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acharyabi/README.md

Abinash Acharya, backends, data pipelines, close to the metal

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I build backend services and data pipelines. Most of my work sits where distributed systems meet large scale data: ingestion that has to stay up, pipelines that move billions of rows, and now and then a microcontroller that needs to figure out where it is.

I would rather compose proven primitives than rebuild what already works.

Outside of that I like building products that make an ordinary day less annoying. I vibe code a lot of them, which gets a rough thing in front of real use quickly, and the parts that survive are the parts worth hardening.

Lately I have been taking breaks to go deeper into systems programming and the fundamentals underneath everything, because I like understanding how the whole universe fits together.

What I reach for

Go Python C
PostgreSQL ClickHouse NATS Kubernetes Docker OpenTelemetry

Where it goes What that looks like
Go Services gRPC, REST and NATS JetStream, with OpenTelemetry wired through from the start
Python Data Prefect, dbt and PySpark feeding ClickHouse and Postgres
C Close to the hardware STM32 firmware, sensor fusion and pose estimation, mostly out of my robotics years

Currently

Trying to understand systems properly, the whole stack of them. POSIX and system calls, networking, and how memory actually behaves, then working up to how the choice of programming language and algorithm shapes the way you end up thinking about a problem.

On the product side I am building a lab report OCR tool, the kind of thing that turns a scanned page of test results into something you can actually read and track.

Alongside that: a Go backend template I actually want to start projects from, and next up a TCP chat server in C, working from raw sockets to a multiplexed server, because some things are worth learning the slow way.

Where I want to end up

Medical research, specifically the part where software and hardware together change how someone actually lives. Sensors, signal processing, and pipelines that turn messy clinical data into something a person can act on. That is what I would like to spend my working life on.

So I am open about it: I am looking for opportunities and partnerships in that space, and for a proper mentor working in it. If that is you, I would like to talk.

Got an idea?

If there is something small and annoying in your day that software should have fixed by now, I would genuinely like to hear about it. Some of them turn into real projects.

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  1. Text-Data-Cleaning Text-Data-Cleaning Public

    Pre-processing Text Data In Multiple Language(tested in Nepali).

    Jupyter Notebook

  2. Stream_Processing_Kafka Stream_Processing_Kafka Public

    Kafka and Spark Structured Streaming on Docker, with Avro and JSON producer/consumer examples

    Python

  3. Deployment-Using-DBT-Cloud Deployment-Using-DBT-Cloud Public

    Trying out deployment using DBT cloud for the ny_taxi rides tlc data.

  4. Batch_Processing_Pyspark Batch_Processing_Pyspark Public

    PySpark batch processing: schemas, Spark SQL, joins, and jobs running on Google Cloud with BigQuery

    Jupyter Notebook

  5. Tweet_Emotion_Detection-Using-TensorFlow Tweet_Emotion_Detection-Using-TensorFlow Public

    Implementation of LSTM for sentiment detection and classification.

    Jupyter Notebook

  6. golang-template golang-template Public

    Personal Go backend template: Echo + GORM + Postgres + OTel (Tempo/Loki/Prometheus/Grafana)

    Go