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2892- Databricks Engineer

7 years

0 Lacs

pune maharashtra india

Posted:5 days ago| Platform: Linkedin logo

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Skills Required

databricks data engineering analytics spark combination design etl apache processing governance efficiency storage testing pyspark scala architecture azure aws gcp workflow orchestration airflow adf git devops cataloging security

Work Mode

On-site

Job Type

Full Time

Job Description

About the Role

Databricks Engineer


Key Responsibilities

  • Design, develop, and maintain

    data pipelines

    and

    ETL/ELT processes

    using Databricks and Apache Spark.
  • Build and optimize

    Delta Lake-based data architectures

    for scalable and reliable analytics.
  • Implement

    data ingestion, transformation, and processing frameworks

    from structured and unstructured sources.
  • Collaborate with data scientists, analysts, and business stakeholders to deliver

    data-driven solutions

    .
  • Ensure

    data quality, governance, and security

    across all platforms and solutions.
  • Optimize

    performance, cost-efficiency, and scalability

    of Databricks workloads.
  • Work with

    cloud platforms

    for data storage, compute, and orchestration.
  • Implement

    CI/CD pipelines, testing frameworks, and MLOps practices

    for Databricks projects.
  • Troubleshoot issues and provide

    production support

    for Databricks environments.


Required Skills & Experience

  • 5–7 years

    of experience in data engineering, with at least

    2–3 years of Databricks hands-on experience

    .
  • Strong expertise in

    Apache Spark (PySpark/Scala/SQL)

    and distributed data processing.
  • Solid experience with

    Delta Lake, Lakehouse architecture, and data modeling

    .
  • Hands-on experience with at least one cloud platform:

    Azure Data Lake, AWS S3, or GCP BigQuery/Storage

    .
  • Strong proficiency in

    SQL

    for data manipulation and performance tuning.
  • Experience with

    ETL frameworks, workflow orchestration tools

    (Airflow, ADF, DBX Workflows).
  • Good understanding of

    CI/CD, Git-based workflows, and DevOps practices

    .
  • Exposure to

    MLOps and MLflow

    is a strong plus.
  • Knowledge of

    data governance, cataloging, and security frameworks

    .

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