Seeking Strong Middle Data Engineers with deep experience in distributed data systems, Spark-based data processing, and production-grade data platform engineering. These engineers will be expected to operate independently, own technical solutions end-to-end, and contribute to both system design and implementation in a highly automated development environment.

What project we have for you

These are hands-on strong middle engineering roles focused on building, scaling, and maintaining large-scale data platforms. Engineers will work on high-priority initiatives involving customer data, data pipeline expansion, compliance-related data engineering, new data source integration, and platform modernization.

The environment is evolving toward a spec-led, agentic development model where engineers spend significant time defining requirements, designing data models, writing technical specifications, reviewing generated code, and ensuring overall solution quality rather than manually writing all application code.

What you will do

- Develop and maintain batch and streaming data pipelines using Scala and Spark.
- Build and support Kafka-based data processing solutions.
- Create and maintain Airflow DAGs and workflows.
- Implement data models, schema mappings, and validation checks.
- Monitor pipeline health, troubleshoot production issues,



and support deployments.
- Review and validate AI-generated code and proposed implementations.
- Collaborate with senior engineers, product teams, and data consumers.

What you need for this

Requirements

- 3+ years of Data Engineering experience.
- Hands-on Scala and Apache Spark experience.
- Experience with batch processing and distributed data systems.
- Kafka, Kafka Streams, Flink, or similar streaming technologies.
- Apache Airflow.
- Data modeling, SQL, and ETL/ELT development.
- Experience with testing, code reviews, version control, and CI/CD.
- Strong troubleshooting and production support skills.
- Positive communication skills and ownership mindset.

Nice to Have

- Flink experience.
- Cassandra, DynamoDB, ScyllaDB, or other NoSQL databases.
- Customer data, clickstream, loyalty, booking, or transactional data experience.
- Experience with Copilot, Claude, Cursor, or other AI-assisted development tools.
- Understanding of data quality monitoring and observability.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Strong Middle Data Engineer (India)
🏢 Intellias
📍 India