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Job Description

Job 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.


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