Description :

Key Responsibilities :

- Develop and maintain batch & streaming data pipelines from transactional, clickstream, and third-party sources.

- Work on data lake / lakehouse / warehouse environments across cloud platforms (e.g., AWS, Azure, Google Cloud Platform (GCP)).

- Build data models and implement medallion architecture (Bronze / Silver / Gold).

- Ensure data quality, reliability, lineage, and performance.

- Follow best practices for data governance, security, and PII handling.

- Collaborate with architects, analysts, and ML teams to deliver scalable data solutions.

- Optimize SQL, ETL/ELT workflows, and orchestration jobs for efficiency.

Required Skills:

- 3 - 4 years of experience in data engineering.

- Strong SQL & Python skills.

- Experience with streaming tools (Kafka, PubSub, Spark, Flink).

- Hands-on experience in building cloud-based data pipelines.

- Knowledge of data modeling : dimensional, data vault, medallion.

- Familiarity with lakehouse/warehouse tools (Databricks, Snowflake, BigQuery, Redshift, ClickHouse).

- Experience with orchestration tools (Airflow, Cloud Composer, etc.).

- Understanding of data governance, lineage, and privacy concepts (GDPR/CCPA).

- Experience with e-commerce or digital data is a plus.