Data Engineer (8+ Years Experience) – Heavy Data Analytics Project
Tech Stack: Spark, PySpark, Scala, Python, SQL, Databricks, Data Lake, Data Warehouse, Snowflake, Azure (ADF/Synapse/ADLS)
Expected Skill set as per customer– Azure Databricks, Spark, Python, Delta Table, Snowflake basics, and prior experience on data ingestion/transformation.
About the Role
We are hiring a Data Engineer with strong hands-on experience in building high‑performance data pipelines for a heavy data analytics project. The candidate must be excellent at writing complex aggregations, understanding business processes and analytical requirements, and designing scalable data lake and data warehouse solutions. Experience across multiple data platforms (Databricks, Snowflake, Azure Data Factory, Synapse, etc.) is a solid advantage.
Key Responsibilities
1. Data Pipeline & ETL/ELT Development
• Develop, optimize, and productionize Spark (PySpark/Scala) pipelines.
• Ingest, transform, cleanse, and aggregate large datasets from varied sources.
• Implement scalable ETL/ELT logic for batch and near-real-time pipelines.




• Apply best practices in partitioning, caching, Delta Lake optimization, and performance tuning.
2. Heavy Data Analytics & Business Understanding
• Write complex aggregation logic (window functions, rollups, grouping sets, analytical functions).
• Understand business KPIs, metrics, and analytical use cases.
• Translate business needs into technical transformations and data models.
• Validate data outputs against business logic and analytics expectations.
• Collaborate with analysts on calculations: weekly/monthly aggregates, trend lines, performance metrics, dimensional rollups.
• Ensure accuracy, consistency, and traceability of business-critical metrics.
3. Data Lake Engineering
• Build and maintain multi-layer Data Lake architectures (Bronze/Silver/Gold).
• Work with Parquet, Delta Lake, ORC, and columnar storage formats.
• Implement schema evolution, auditing, and metadata strate

📌 Opportunity for Data Engineer (India)
🏢 Hinduja Tech
📍 India