We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and platforms.
You will work closely with data scientists, analysts, and business stakeholders to ensure reliable, high-quality data across our ecosystem.
Responsibilities :
- Design and develop robust ETL/ELT pipelines using PySpark and SQL for large-scale data processing.
- Build, manage, and optimise data workflows on Databricks, including notebooks, jobs, and cluster configurations.
- Collaborate with analytics and ML teams to deliver clean, well-documented datasets.
- Monitor pipeline performance, troubleshoot failures, and ensure data quality and integrity.
- Define and implement data governance and best practices across the data platform.
- Participate in design reviews and contribute to architectural decisions.
Requirements :
- 4 - 6 years of hands-on experience in data engineering or a related role.
- Robust proficiency in PySpark for large-scale distributed data processing.
- Advanced SQL skills - query optimisation, window functions, CTEs, and complex joins.
- Solid experience with Databricks - Delta Lake, workflows, Unity Catalog preferred.
- Experience working with cloud platforms (AWS/Azure).
Nice to have :
- Experience with streaming frameworks such as Apache Kafka or Spark Streaming.
- Exposure to ML pipelines and feature engineering workflows.
📌 Expleo - Data Engineer - PySpark (India)
🏢 Expleo Solutions
📍 India
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