Lead - Data Engineering

Role Summary

Data Engineering Lead

Key Responsibilities

• Design and implement scalable data architectures using

  Hive, ClickHouse, Spark, and DWH

• Lead development of batch and near-real-time data pipelines
• Define data modelling standards for analytical and reporting use cases
• Optimize query performance, storage, and compute cost
• Ensure data quality, consistency, and reliability

Engineering & Delivery

• Own end-to-end delivery of data engineering workstreams
• Review design, code, and data models
• Drive performance tuning and capacity planning
• Handle production issues and root-cause analysis

Team & Stakeholder Management

• Mentor and guide data engineers
• Break down requirements into executable tasks
• Work closely with business, analytics, and application teams
• Communicate progress, risks, and dependencies clearly

Technical Skills (Must Have)

• Strong experience with

  Apache Spark (PySpark / Scala)

• Hands-on expertise in

  Hive

  and

  ClickHouse

• Strong

  Data Warehousing

  concepts (facts, dimensions, star schema)
• SQL expertise and performance tuning
• Experience building ETL / ELT pipelines
• Linux and scripting (Shell / Python)

Good to Have

• Experience with streaming platforms (Kafka, similar)
• Cloud data platforms (AWS / Azure)
• Exposure to BI and analytics workloads
• Experience handling large-scale datasets (TB/PB range)