Data Engineer – Databricks & Lakehouse

Inactive
Remote opportunity based in IndiaFull-TimeSenior
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Salary not disclosed
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Job Details

Experience
8+ years
Required Skills
PythonSQLMicrosoft Power BISparkCI/CDDevOpsData modelingDatabricks

Requirements

  • 8+ years of experience in data engineering or related roles within large-scale enterprise environments.
  • Strong hands-on experience with Databricks, Apache Spark, and Delta Lake.
  • Advanced proficiency in SQL and Python for data processing and pipeline development.
  • Experience working with Power BI or similar BI and visualization tools.
  • Solid understanding of data modeling, business logic translation, and enterprise data architecture.
  • Experience with cloud data platforms such as Azure Data Factory, Synapse, or data lake environments.
  • Familiarity with CI/CD pipelines, DevOps practices, and automated deployment workflows.
  • Strong analytical and problem-solving skills.
  • Exposure to AI-assisted development tools is a plus.

Responsibilities

  • Design, build, and maintain scalable data pipelines using Databricks, Spark, and Delta Lake within a Lakehouse architecture.
  • Develop and manage bronze, silver, and gold layer transformations, ensuring optimized performance, reliability, and cost efficiency.
  • Integrate data from enterprise systems such as ERP, CRM, APIs, and other internal platforms into unified data models.
  • Build curated, business-ready datasets aligned with standardized definitions and Power BI semantic models.
  • Implement data quality checks, validation rules, and testing frameworks to ensure production-grade reliability.
  • Monitor pipeline performance, troubleshoot issues, and maintain consistency across development, testing, and production environments.
  • Collaborate with BI teams, business stakeholders, and governance functions to ensure accurate and well-documented data models.
  • Contribute to CI/CD practices, deployment processes, and data lineage tracking for improved transparency and control.
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