Data Engineer 6+

Hybrid(Bangalore)

12 months C2H

Key Responsibilities

Design and develop data pipelines (batch and streaming) using Databricks and PySpark.

Write optimized PySpark code to process large datasets.

Build and manage CI/CD pipelines for data workflows using GitHub / GitHub Actions / Azure DevOps.

Implement data validation and data quality checks.

Monitor pipelines using logging, alerting, and observability tools.

Collaborate with cross-functional teams and document data pipeline architecture.

Mandatory Skills

4–5 years of Data Engineering experience

Databricks

PySpark

End-to-end Data Pipeline Development (Batch / Streaming)

GitHub (branching, pull requests, code reviews)

CI/CD for Data Pipelines (GitHub Actions / Azure DevOps)

Data Validation / Data Quality Frameworks

Pipeline Monitoring (Logging, Alerting, SLA tracking)

Apache Kafka

Data Warehousing / Lakehouse Architecture concepts

MongoDB or other NoSQL databases

Data Governance

Data Modeling

Spark Streaming

📌 Data Engineer (India)
🏢 Sparix Global
📍 India