Data Engineer (3 - 4 Years)
Responsibilities
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This is a hands-on engineering role where you will actively build and write production code - not just manage or delegate.
Design, build, and maintain scalable batch and near real-time data pipelines.
Develop ETL/ELT pipelines using Python, SQL, and Spark/PySpark on Databricks.
Build Bronze, Silver, and Gold data models using a Lakehouse (Medallion) architecture.
Optimize Spark jobs for performance, scalability, and cost.
Work with structured and semi-structured datasets from multiple sources.
Develop reusable, production-ready data engineering frameworks.
Own data quality, monitoring, and pipeline reliability as measurable outcomes.
Collaborate closely with Product, Analytics, and Business teams.
Participate in code reviews and production support.
Navigate our current stack: Spark, Databricks, Delta Lake (Medallion architecture), BigQuery, Airbyte, and Power BI.
Requirements




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3+ years of qualified experience in Data Engineering, with a robust software engineering foundation.
Robust SQL skills (joins, CTEs, window functions, query optimization).
Hands-on Python programming skills.
Hands-on experience with Apache Spark / PySpark / Databricks.
Solid knowledge of data warehousing and data modeling.
Experience with ETL/ELT and incremental data processing.
Experience with the AWS or GCP cloud ecosystem.
Strong communication skills - you can translate between data engineering and business/analytics stakeholders.
Good to Have
Airbyte, Kafka, or CDC concepts.
Delta Lake or Apache Iceberg.
Airflow or Databricks Workflows.
Docker / Kubernetes.
Performance tuning and partitioning strategies.

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📌 Senior Data Engineer Gurugram (India)
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📍 India