10 Sql Clustering Jobs nearby Anand

As a Full-Stack Technical Lead at our company, your role will involve guiding the engineering team to build scalable and highly available systems. You will need to utilize your deep technical expertise along with leadership skills to mentor developers and drive architectural decisions. Key Responsibilities: - Lead and mentor a team of full-stack developers to ensure efficient project delivery. - Design and architect highly available, scalable, and fault-tolerant systems. - Make key technical decisions regarding the technology stack and architecture patterns. - Develop frontend and backend components using Node.js, Java, React, and Angular. - Implement high availability architecture and disaster recovery strategies for robust systems. - Conduct code reviews to maintain code quality standards and consistency. - Define and implement best practices for development, testing, and deployment processes. - Collaborate with product managers and stakeholders to define the technical roadmap for projects. - Optimize system performance, scalability, and reliability for enhanced user experience. - Troubleshoot complex technical issues and provide effective solutions. - Establish monitoring, logging, and alerting strategies for proactive system management. - Drive continuous improvement in development processes to enhance productivity. - Participate actively in sprint planning, stand-ups, and retrospectives. - Stay updated with emerging technologies and evaluate their applicability in projects. Qualifications Required: - 7-9 years of software development experience with a minimum of 2 years in a technical leadership role. - Strong expertise in Node.js and Java for backend development. - Proficiency in React and Angular for frontend development. - Deep understanding of High Availability architecture including load balancing, failover strategies, database replication, caching strategies, microservices architecture, and more. - Experience designing and implementing distributed systems. - Strong knowledge of both SQL and NoSQL database technologies. - Experience with cloud platforms such as AWS, Azure, and GCP, along with their High Availability services. - Understanding of DevOps practices and CI/CD pipelines. - Excellent problem-solving and analytical skills. - Strong communication and leadership abilities. - Experience with Agile/Scrum methodologies. The above description outlines the key responsibilities and qualifications required for the role of Full-Stack Technical Lead at our company.,

As a member of the data science team, you will have the opportunity to work on cutting-edge analytics technologies, develop predictive models, and contribute to data-driven decision making. The role focuses on end-to-end data science workflows, advanced statistical analysis, and real-world AI applications in business contexts. Key Responsibilities: - Conduct comprehensive data collection, cleaning, preprocessing, and exploratory data analysis using Python, R, and SQL frameworks. - Develop and implement machine learning models for classification, regression, clustering, and time-series forecasting applications. - Create advanced data visualizations and interactive dashboards using Tableau, Power BI, matplotlib, and seaborn libraries. - Perform statistical analysis, hypothesis testing, and A/B testing to derive actionable business insights. - Build and deploy predictive analytics models to support business strategy and operational optimization. - Collaborate with cross-functional teams to translate business requirements into analytical solutions and recommendations. - Document analytical processes, create technical reports, and present findings to stakeholders through compelling data storytelling. Qualifications Required: Must-Haves: - Bachelors or Masters degree in Data Science, Statistics, Computer Science, Mathematics, or related field (final year students or recent graduates). - Strong programming proficiency in Python with experience in NumPy, Pandas, Scikit-learn, and Jupyter Notebooks. - Solid understanding of statistical concepts including descriptive statistics, probability distributions, and inferential statistics. - Knowledge of SQL for database querying and data manipulation from various data sources. - Experience with data visualization tools and techniques for creating meaningful insights from complex datasets. Nice-to-Haves: - Hands-on experience with machine learning frameworks like TensorFlow, PyTorch, or advanced scikit-learn applications. - Familiarity with cloud platforms (AWS, GCP, Azure) for data processing, model deployment, and distributed computing. - Knowledge of big data technologies including Spark, Hadoop, or NoSQL databases for large-scale data processing. - Experience with advanced analytics techniques including deep learning, NLP, or computer vision applications. - Previous internship experience or portfolio projects demonstrating real-world data science problem-solving capabilities.,

As an MS-SQL Database Administrator, your role will involve the installation, configuration, and upgrading of MS-SQL server, SSRS, and IIS, as well as web services and related products. You will be responsible for troubleshooting and problem-solving of MS-SQL server and databases, while also periodically monitoring databases for performance improvements. Your tasks will include maintaining and enhancing databases through rollout and updates, coding, monitoring, and tuning database objects for optimal performance. Additionally, you will control user privileges and resources, maintain overall security of databases, and assist in database and resource capacity planning. Your responsibilities will also entail assisting project managers and business analysts with reporting requirements, designing and testing backup and restore procedures, and developing an Enterprise Security Policy for database systems. You will be expected to perform problem determination and troubleshooting of technical issues, monitor and train support staff on basic MS-SQL commands and procedures, and ensure system performance meets specifications through debugging and fine-tuning the environment. Furthermore, you will need to define, document, and create backup procedures for full database recoveries, review and develop new stored procedures for developers, and provide on-call support for systems and associated software products on a 24/7 rotation basis. Key Responsibilities: - Installation, configuration, and upgrading of MS-SQL server, SSRS, and IIS, along with web services and related products - Troubleshooting and problem-solving of MS-SQL server and databases - Periodic monitoring of databases for performance improvements - Maintenance and improvement of databases through rollout and updates - Coding, monitoring, and tuning database objects for optimal performance - Controlling user privileges and resources, maintaining overall security of databases - Assisting in database and resource capacity planning - Assisting project managers and business analysts with reporting requirements - Designing and testing backup and restore procedures for databases - Developing an Enterprise Security Policy for database systems - Performing problem determination and troubleshooting of technical problems - Monitoring and training support staff on basic MS-SQL commands and procedures - Ensuring system performs to specifications through debugging and fine-tuning environment - Defining, documenting, and creating backup procedures for full database recoveries - Reviewing and developing new stored procedures for developers - Providing on-call support for systems and associated software products on a 24/7 rotation basis Qualifications Required: - Strong knowledge of backups, restores, recovery models, database shrink operations, DBCC commands, Clustering, Database mirroring, Replication, and High Availability strategies for MS SQL environments - Ability to identify and troubleshoot SQL Server related CPU, Memory, I/O, disk space, and other resource contention - Experience with MS SQL Server backup and recovery techniques in a clustered VLDB environment - Experience with Sequel Services Integration Services (SSIS), OLAP services (SSAS), Reporting services (SSRS), and Oracle Business Intelligence reporting tool (Hyperion) in a data warehousing environment - SQL Development ability to write and troubleshoot SQL Code and design - Experience in creating database architecture with associated schema as part of a software design process - Understanding of database design practices, including database normalization concepts - Knowledge of SQL Server tools such as Profiler, DTA, SSMS, SAC, SSCM, PerfMon, DMVs, system sprocs, etc.,

We are currently hiring for "SQL Server Database Administrator" post in Ahmedabad. Company Profile: Cloud technology based information technology (IT) company Designation: SQL Server Database Administrator (JIS60878)Location: AhmedabadExperience Range: 4.0 To 6.0 yrs Job Profile:We are seeking a skilled SQL Server database administrator (minimum 3 years of hands-on experience)The DBA position will be responsible for maintaining the companys database systems including back-up, performance tuning, capacity planning, monitoring critical events, and documentation. The position will be required to work on numerous projects at the same time, responding to various demands from different departments. Position Requirements: T-SQL and DBA experience is a mandatory requirement. Strong experience in Database Administration in SQL Server (2008 to 2014)Experience in troubleshooting and resolving database integrity issues, performance issues, blocking and deadlocking issues, replication issues, log shipping issues, connectivity issues, security issues etc.Experience in Performance Tuning, Query Optimization, using Performance Monitor, SQL Profiler and other related monitoring and troubleshooting tools.Ability to detect and troubleshoot SQL Server related CPU, memory, I/O, disk space and other resource contention.Strong knowledge of backups, restores, recovery models, database shrink operations, DBCC commands, Clustering, Database mirroring, Replication.Experience in managing version control for SQL Server stored procedures.Strong knowledge of how indexes, index management, integrity checks, configuration, patching. How statistics work, how indexes are stored, how they can be created and managed effectively.Knowledge of SQL Server tools ( Profiler, DTA, SSMS, SAC, SSCM, PerfMon, DMVs, system stored procs)Administering maintaining System stored procedures and tablesAdministering SQL server accessAdministering SQL server securitySQL Development ability to write and troubleshoot SQL Code and design ( stored procs, functions, tables, views, triggers, indexes, constraints )Knowledge of windows server, security, SPNs, storage components in relation to maintaining the SQL server.Documentation skills for processes and procedures ( creating KBs, runbooks, topology etc )SQL Database Operational support to tech usersAbility to adapt quickly to an existing, complex environment.Ability to quickly learn new concepts and software tools where necessary.Candidate should be a self-motivated, independent, detail oriented, responsible team-player and exhibit exceptional relationship management skills. (Working Hours/Timing:1:30 pm to 10:30 pm 6 months and 2:30 pm to 11:30 pm 6 months due to daylight UK timing) Interested candidate can send their resume on varsha@postaresume.co.inCall now on +91- 6354797016

As a Data Scientist at our company, you will be responsible for translating real-world problems into well-structured mathematical/statistical models. You will design and implement algorithms using linear algebra, optimization, and probability theory. Your role will involve developing predictive and classification models using ML techniques such as regression, trees, neural networks, and clustering. Additionally, you will conduct exploratory data analysis and feature engineering on large datasets. You will use hypothesis testing, inferential statistics, and confidence intervals to validate results and collaborate with product and engineering teams to integrate models into production pipelines. Key Responsibilities: - Translate real-world problems into mathematical/statistical models - Design and implement algorithms using linear algebra, optimization, and probability theory - Develop predictive and classification models using ML techniques - Conduct exploratory data analysis and feature engineering - Collaborate with product and engineering teams Qualifications Required: - Strong understanding of Linear Algebra, Multivariable Calculus, Probability & Statistics - Hands-on experience with statistical inference, hypothesis testing, and confidence intervals - Practical knowledge of supervised and unsupervised learning - Comfortable with algorithms like regression, SVMs, decision trees, clustering - Proficient in Python (NumPy, Pandas, Scikit-learn, Statsmodels) - Experience with ML libraries like TensorFlow, PyTorch - Strong analytical and critical thinking skills - Ability to convert vague requirements into well-defined problems - Exposure to graph theory, time-series analysis, or numerical methods would be a plus If you are looking for a challenging role where you can utilize your mathematical, statistical, and machine learning skills to solve real-world problems, then this position is perfect for you. Join our team and be part of cutting-edge projects that make a difference. (Note: The additional details of the company are not provided in the job description.),

As a highly experienced and strategic Snowflake Architect, your role will involve designing, implementing, and leading robust, scalable, and secure cloud-based data platforms. You will be responsible for defining the enterprise data architecture using Snowflake and modern cloud platforms. Additionally, you will design and manage the implementation of high-performance ELT/ETL pipelines, provide architectural guidance on data modeling, data mesh, and data lake structures, and ensure cost optimization, platform security, and scalability across deployments. Your collaboration with cross-functional teams (Product, BI, DevOps, Security) will be crucial for smooth delivery. Furthermore, you will drive the adoption of Snowflake best practices, version upgrades, and feature enablement, as well as review and approve data solution architectures to ensure alignment with business goals. Your key responsibilities will include: - Define the enterprise data architecture using Snowflake and modern cloud platforms - Design and manage implementation of high-performance ELT/ETL pipelines - Provide architectural guidance on data modeling, data mesh, and data lake structures - Ensure cost optimization, platform security, and scalability across deployments - Collaborate with cross-functional teams for smooth delivery - Drive adoption of Snowflake best practices, version upgrades, and feature enablement - Review and approve data solution architectures and ensure alignment with business goals To excel in this role, you should possess the following qualifications: - 10+ years of experience in data engineering or architecture - Minimum 4+ years of hands-on experience with Snowflake - Deep expertise in Snowflake internals, storage architecture, caching, clustering, and performance tuning - Strong understanding of data architecture principles including data lakes, data mesh, dimensional modeling - Proven experience integrating Snowflake with tools like Kafka, Airflow, dbt, Fivetran, etc. - Proficiency in SQL, Python, and cloud ecosystems (AWS, Azure, or GCP) - Familiarity with DevOps/IaC tools like Terraform Preferred skills for this role include experience with data governance tools (e.g., Collibra, Alation), SnowPro Advanced Architect or other relevant Snowflake certifications, and hands-on leadership in large-scale data platform migrations or cloud modernization initiatives. Educational Qualifications: - Bachelors or Masters degree in Computer Science, Engineering, or a related field If you join us, you will: - Lead mission-critical data initiatives with cutting-edge cloud tools - Collaborate with passionate engineering and analytics professionals - Enjoy competitive contract engagement with flexibility and autonomy Please note that the work location for this full-time position is in person. Benefit: - Health insurance As a highly experienced and strategic Snowflake Architect, your role will involve designing, implementing, and leading robust, scalable, and secure cloud-based data platforms. You will be responsible for defining the enterprise data architecture using Snowflake and modern cloud platforms. Additionally, you will design and manage the implementation of high-performance ELT/ETL pipelines, provide architectural guidance on data modeling, data mesh, and data lake structures, and ensure cost optimization, platform security, and scalability across deployments. Your collaboration with cross-functional teams (Product, BI, DevOps, Security) will be crucial for smooth delivery. Furthermore, you will drive the adoption of Snowflake best practices, version upgrades, and feature enablement, as well as review and approve data solution architectures to ensure alignment with business goals. Your key responsibilities will include: - Define the enterprise data architecture using Snowflake and modern cloud platforms - Design and manage implementation of high-performance ELT/ETL pipelines - Provide architectural guidance on data modeling, data mesh, and data lake structures - Ensure cost optimization, platform security, and scalability across deployments - Collaborate with cross-functional teams for smooth delivery - Drive adoption of Snowflake best practices, version upgrades, and feature enablement - Review and approve data solution architectures and ensure alignment with business goals To excel in this role, you should possess the following qualifications: - 10+ years of experience in data engineering or architecture - Minimum 4+ years of hands-on experience with Snowflake - Deep expertise in Snowflake internals, storage architecture, caching, clustering, and performance tuning - Strong understanding of data architecture principles including data lakes, data mesh, dimensional modeling - Proven experience integrating Snowflake with tools like Kafka, Airflow, dbt, Fivetran, etc. - Proficiency in SQL, Python, and cloud ecosystems (AWS, Azure, or GCP) - Familiarity with DevOps/IaC tools like Terraform Preferred skills for this ro

As a Senior Software Engineer (Machine Learning) at our company, you will be responsible for designing, building, and deploying scalable ML-based systems and services. Your role will involve working across the entire ML lifecycle, from data ingestion and feature engineering to model development, optimization, and deployment, with a focus on delivering high-quality, production-grade solutions. **Key Responsibilities:** - **Machine Learning Development:** - Design and implement machine learning models and algorithms for predictive analytics, classification, clustering, or recommendation systems. - Optimize models for accuracy, performance, and scalability in production environments. - Develop automated pipelines for model training, validation, and deployment (ML pipelines). - Conduct feature selection, model tuning, and hyperparameter optimization. - Collaborate with data scientists to transition research models into production-ready services. - **Engineering & Deployment:** - Build and maintain APIs or microservices for model inference and integration with other systems. - Work closely with DevOps to deploy, scale, and monitor ML workloads on cloud platforms (AWS/Azure). - Ensure proper data handling, storage, and lineage across training and inference pipelines. - **Data Engineering & Collaboration:** - Work with data engineers to build and optimize ETL/ELT pipelines for ML-ready data. - Ensure data quality, consistency, and governance throughout the ML lifecycle. - Collaborate with cross-functional teams to define problem statements, metrics, and success criteria. - **Innovation & Continuous Improvement:** - Explore and evaluate new ML techniques, frameworks, and architectures. - Drive automation and standardization in ML workflows to improve efficiency. - Contribute to the organization's engineering best practices and knowledge sharing. **Qualifications Required:** - **Core Technical Skills:** - 4 to 6 years of experience in software engineering, with at least 2 years in machine learning development. - Proficiency in Python and key ML libraries like Scikit-learn, TensorFlow, or PyTorch. - Strong understanding of data preprocessing, feature engineering, and model lifecycle management. - Proficiency in SQL and exposure to NoSQL systems. - Experience building APIs or backend services using frameworks like FastAPI, Flask, or Django. - **Cloud Exposure:** - Working knowledge of AWS Sagemaker/Azure ML. - Experience in containerization (Docker, Kubernetes) and integrating ML models into production systems. - Familiarity with CI/CD tools and version control (Git). - **LLM & AI Awareness (Preferred):** - Awareness of Large Language Models (LLMs) such as OpenAI, LLaMA, and Bedrock. - Ability to evaluate and recommend the appropriate model for a given use case. - **Visualization & Communication:** - Experience using Power BI, Tableau, or Python visualization tools. This job provides an exciting opportunity for an experienced engineer to combine machine learning expertise with solid software engineering skills while collaborating with data scientists and engineering teams to deliver innovative solutions.,

You are being sought for the role of Marketing Data Analyst at Uplers, where you will be responsible for developing and providing data-driven insights on email, SMS, and other marketing channel performance for clients. Your tasks will include building and optimizing measurement frameworks and dashboards, analyzing data from various sources, and delivering actionable insights to enhance client ROI. You will collaborate closely with Program Directors, assisting in strategic initiatives, identifying key metrics, advising on improvements, and ensuring compliance with industry regulations. This position is ideal for individuals passionate about leveraging data to address clients" critical questions. **Roles & Responsibilities:** - Creating and distributing standard reporting frameworks and dashboards for client teams to facilitate message and campaign reporting on a large scale. - Gathering and analyzing data from multiple sources, including email and marketing automation tools, web analytics, and more. - Assisting Program Directors in onboarding new clients by understanding their data needs, aligning on key performance metrics, and agreeing on essential reports. - Supporting Program Directors in establishing testing protocols and test designs for accurate tracking and measurement. - Developing ongoing learning roadmaps and strategies alongside Program Directors to drive continuous improvement and program optimization. - Analyzing customer and program performance data to identify trends and audience segments. - Monitoring industry trends and best practices to enhance strategic recommendations. **Required Skills:** - MBA or equivalent experience. - 3-4 years of experience in data science, analytics, or data strategy demonstrating the ability to interpret data and deliver actionable insights. - Experience in email marketing analytics is advantageous. - Proficiency in marketing analytics and marketing automation tools like Salesforce, Braze, HubSpot, web analytics, CRMs, and data visualization tools such as Tableau, PowerBI, Looker Studio, etc. - Strong knowledge of SQL and experience with data platforms like BigQuery, Snowflake, Databricks, and Redshift. - Familiarity with predictive modeling, clustering, regression analysis, decision trees, and machine learning libraries. - Excellent written and oral communication skills, especially in a business setting. Ability to communicate with technical and non-technical audiences is a plus. - Strong project management skills, adaptability to changing deadlines, priorities, and project requirements. - Effective time management skills, capable of handling multiple projects and clients simultaneously. - Experience working with a fully remote team, including overseas team members. If you are prepared for a new challenge, a supportive work environment, and an opportunity to advance your career, don't hesitate to apply for this role at Uplers. Your application will help you discover and apply for relevant contractual onsite opportunities and progress in your career with our assistance. We are ready to support you through any challenges or grievances you may encounter during your engagement. Apply today and take the next step in your career with us!,

You are a highly skilled Data Scientist & AI Engineer who is passionate about solving real-world problems using data, machine learning, and cutting-edge AI technologies. This role offers you the opportunity to work on advanced predictive modeling, Generative AI, and Natural Language Processing (NLP), while collaborating with cross-functional teams to deliver innovative solutions. Key Responsibilities - Design, develop, and deploy predictive models and machine learning algorithms for classification, regression, and clustering. - Build and optimize Retrieval-Augmented Generation (RAG) pipelines and scalable systems using large language models (LLMs). - Fine-tune and customize LLMs to align with specific business use cases. - Explore and evaluate open-source LLMs to stay ahead of emerging AI advancements. - Apply traditional NLP techniques (e.g., BERT, text classification, sentiment analysis, NER). - Develop and maintain APIs for AI models using frameworks such as FastAPI, ensuring scalability and reliability. - Collaborate with data scientists, product managers, and engineers to integrate AI-driven features into products. - Perform data preprocessing, feature engineering, and validation for ML/AI models. - Document solutions and communicate insights clearly to both technical and business stakeholders. - Continuously improve models, pipelines, and analytics processes. Technical Skills - Strong programming skills in Python with libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn. - Solid experience with SQL for data extraction and transformation. - Hands-on experience building and tuning supervised & unsupervised ML models. - Understanding of model evaluation metrics (accuracy, precision, recall, F1-score, ROC-AUC). - Familiarity with GenAI concepts and production-grade implementation. - Exposure to traditional NLP or recommendation systems is a plus. - Knowledge of data engineering practices including cleaning, transformation, and pipeline automation. - Experience with version control tools (Git) and Jupyter notebooks. Why Join Us You will have the opportunity to work on cutting-edge AI projects including Generative AI and NLP. Collaborate with a team that values innovation, learning, and impact. Experience a growth-oriented culture with exposure to diverse projects and technologies.,

As a Sr. Data Scientist at our company, you will be responsible for analyzing large datasets, building predictive models, and providing actionable insights that drive strategic decision-making. You will work closely with stakeholders to identify business challenges and translate them into data science problems. Your role will involve extracting insights and building models to understand/predict key metrics, as well as collecting, cleaning, and preprocessing structured and unstructured data from various sources. You will focus on research analysis, model development, and deploying machine learning models to solve real-world business problems. Additionally, you will perform statistical analysis, generate data-driven insights and recommendations, and collaborate with engineering and product teams to implement data solutions. Automating monitoring model performance and retraining will also be part of your responsibilities. Key Responsibilities: - Extract insights & build models to understand/predict key metrics - Work closely with stakeholders to identify business challenges and translate them into data science problems - Collect, clean, and preprocess structured and unstructured data from various sources - Focus on research analysis, model development - Building models (regression, classification, clustering, etc.), validate and deploy machine learning models to solve real-world business problems - Perform statistical analysis and generate data-driven insights and recommendations - Collaborate with engineering and product teams to implement data solutions - Automate monitoring model performance and retraining Required Skills & Qualifications: - Bachelor's or master's degree in computer science, Data Science, Statistics, Mathematics, or a related field - 5+ years of experience in a data science or machine learning role - Strong Python (PySpark, pandas, scikit-learn, TensorFlow/PyTorch) - Hands-on experience with MLflow for model tracking & deployment - Expertise in Databricks for scalable ML workflows - Expertise in handling data issues including data gaps, duplicates, data drifts, etc. - Strong SQL skills and experience working with large databases - Solid understanding of statistical modeling, A/B testing, and predictive analytics - Strong grasp of supervised/unsupervised learning, deep learning, and optimization techniques - Experience with A/B testing and model performance monitoring - Experience with cloud platforms (AWS, GCP, or Azure) and working knowledge of MLOps is a plus - Excellent problem-solving skills, communication skills, and attention to detail - Experience deploying models to production using CI/CD pipelines Preferred Skills (Good to Have): - MosaicML/Azure ML/AWS Sagemaker experience is a plus - Healthcare industry-specific experience In addition to the above, you will enjoy perks such as flexible timings, 5 days working schedule, a healthy environment, celebrations, opportunities for learning and growth, building the community, and medical insurance benefits.,