Data Engineer (Spark | SQL | Big Data Pipelines)

Role: Data Engineer (Spark | SQL | Big Data Pipelines)

Location:

Experience Neeeded:

Note

About the Role

Data Engineer

Key Responsibilities

• Design, build, and optimize

  data pipelines

  for ingestion, transformation, and loading (ETL/ELT).
• Work extensively with

  Spark

  and

  SparkSQL

  for batch data processing.
• Develop and maintain

  efficient SQL queries

  for large-scale data operations.
• Monitor and troubleshoot pipeline performance, dependencies, and data quality issues.
• Collaborate with analytics, data science, and business teams to ensure reliable and accessible data.

Must-Have Skills

• 3–5 years of hands-on experience with

  Apache Spark

  (including

  SparkSQL

  ).

• Strong SQL expertise

  — ability to write complex, optimized queries.
• Solid

  batch processing experience

  (scheduling, dependencies, performance tuning).
• Good understanding of

  data pipeline architecture and fundamentals

  .
• Experience handling structured and semi-structured data (CSV, JSON, Parquet).

Good to Have

• Python or PySpark

  experience (not mandatory but preferred).
• Exposure to

  data warehousing concepts

  and relational databases.

About Client:

A global e-commerce leader enabling millions of buyers and sellers to connect across markets. The platform delivers secure, scalable, and data-driven marketplace experiences. Engineers here build solutions that shape the future of digital commerce through innovation in payments, logistics, AI, and customer experience.