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UIX Labs - Senior Data Engineer
UIX Labs - Senior Data EngineerUIX Labs • Navi Mumbai
UIX Labs - Senior Data Engineer

UIX Labs - Senior Data Engineer

UIX Labs • Navi Mumbai
5 days ago
Job description

JOB DESCRIPTION : Data Engineer

We are seeking a highly skilled Data Engineer with deep expertise in Apache Kafka integration with Databricks, structured streaming, and large-scale data pipeline design using the Medallion Architecture. The ideal candidate will demonstrate strong hands-on experience in building and optimizing real-time and batch pipelines, and will be expected to solve real coding problems during the interview.

Job Description :

  • Design, develop, and maintain real-time and batch data pipelines in Databricks .
  • Integrate Apache Kafka with Databricks using Structured Streaming.
  • Implement robust data ingestion frameworks using Databricks Autoloader.
  • Build and maintain Medallion Architecture pipelines across Bronze, Silver, and Gold layers.
  • Implement checkpointing, output modes, and appropriate processing modes in structured streaming jobs.
  • Design and implement Change Data Capture (CDC) workflows and Slowly Changing Dimensions (SCD) Type 1 and Type 2 logic.
  • Develop reusable components for merge / upsert operations and window function based transformations.
  • Handle large volumes of data efficiently through proper partitioning, caching, and cluster tuning techniques.
  • Collaborate with cross-functional teams to ensure data availability, reliability, and consistency.

Must Have :

  • Apache Kafka : Integration, topic management, schema registry (Avro / JSON).
  • Databricks & Spark Structured Streaming :
  • 1. Processing Modes : Append, Update, Complete

    2. Output Modes : Memory, Console, File, Kafka, Delta

    3. Checkpointing and fault tolerance

  • Databricks Autoloader : Schema inference, schema evolution, incremental loads.
  • Medallion Architecture implementation expertise.
  • Performance Optimization :
  • i. Data partitioning strategies

    ii. Caching and persistence

    iii. Adaptive query execution and cluster configuration tuning

  • SQL & Spark SQL : Proficiency in writing efficient queries and transformations.
  • Data Governance : Schema enforcement, data quality checks, and monitoring.
  • Good to Have :

  • Strong coding skills in Python and PySpark.
  • Experience working in CI / CD environments for data pipelines.
  • Exposure to cloud platforms (AWS / Azure / GCP).
  • Understanding of Delta Lake, time travel, and data versioning.
  • Familiarity with orchestration tools like Airflow or Azure Data Factory.
  • (ref : hirist.tech)

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