Data Engineer (5+)
tieto | 14 days ago | Pune

  • Design, develop and maintain scalable data pipelines using Azure Databricks, PySpark, Python, SQL and Delta Lake.
  • Implement Bronze, Silver and Gold Lakehouse data layers and reusable data-engineering frameworks.
  • Develop complex ETL/ELT solutions involving SAP and other enterprise source systems.
  • Ingest and transform data originating from SAP environments, applying appropriate business and transformation logic.
  • Build data solutions supporting manufacturing business processes, reporting and analytics.
  • Implement batch and incremental data-loading patterns, schema evolution, historical data handling and pipeline recovery.
  • Develop and optimize complex Spark/PySpark workloads and SQL transformations for scalability and performance.
  • Implement data-quality checks, validation, reconciliation, monitoring and exception handling.
  • Develop analytical and dimensional data models, including Fact/Dimension and Star Schema models.
  • Follow engineering best practices for Git, CI/CD, automated deployment, coding standards and documentation.
  • Work with Data Architects and business stakeholders to translate technical and business requirements into scalable data solutions.
  • Participate in design reviews, code reviews and continuous improvement of Databricks engineering practices.

 

Technical Skills & Certifications Essential Skills

  • 5–10 years of experience in Data Engineering, Data Warehousing or Data Platform development.
  • Strong hands-on experience with Azure Databricks.
  • Strong development skills in PySpark, Apache Spark, Python and SQL.
  • Good understanding of Delta Lake and Lakehouse architecture.
  • Experience implementing Bronze, Silver and Gold / Medallion architecture.
  • Strong experience developing enterprise-scale ETL/ELT and data pipelines.
  • Experience with data modelling, including Fact/Dimension models and Star Schemas.
  • Understanding of data quality, governance, metadata, lineage and security concepts.
  • Experience with Git, CI/CD and DevOps practices for data-engineering solutions.
  • Strong troubleshooting, performance optimization and problem-solving skills.
    • Good communication skills and ability to work with globally distributed technical and business teams.
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