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Achievements

Achievement: Pull SharkAchievement: Arctic Code Vault Contributor

Achievements

Achievement: Pull SharkAchievement: Arctic Code Vault Contributor

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Indra333/README.md

Indrasenareddy Annapureddy

Data Engineer with 5+ years of experience building scalable batch and streaming data pipelines. I work across the modern data stack, turning raw data into reliable, well-tested analytics products from ingestion and orchestration through modeling and serving.

Currently a Data Engineer at Progressive Insurance, where I design and operate production ETL/ELT pipelines.

Open to new opportunities reach me on LinkedIn.

Stack

Python SQL Apache Spark Kafka Airflow dbt Databricks Snowflake AWS Azure

Pinned projects

A few portfolio builds that show how I work:

  • pyspark-etl-pipeline end-to-end batch ETL in PySpark with SCD Type 1 handling, partitioned Parquet output, data-quality gates, and pytest coverage.
  • airflow-data-pipelines production-style Airflow DAGs: a daily ETL with retries and SLAs, plus a backfill-friendly partitioned pipeline.
  • dbt-analytics-engineering layered dbt project (staging → intermediate → marts) with data tests and docs, running locally on DuckDB.

Pinned Loading

  1. airflow-data-pipelines airflow-data-pipelines Public

    Production-style Apache Airflow DAGs: daily ETL with retries/SLAs and backfill-friendly partitioned pipelines.

    Python

  2. dbt-analytics-engineering dbt-analytics-engineering Public

    dbt analytics engineering project: staged, tested, documented marts (runs locally on DuckDB).

  3. pyspark-etl-pipeline pyspark-etl-pipeline Public

    End-to-end batch ETL pipeline with PySpark: CSV ingestion, transformations, SCD handling, partitioned Parquet output and data-quality checks.

    Python