AI and Data ETL Architect
If you are available for a Face to face interview on 10th Jan Saturday In Pune. Then please share your CV to [Confidential Information] with the below details:
Total Experience-
Current CTC-
Expected CTC-
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If shortlisted you will be invited for a F2F interview
Role Context
Own ETL architecture patterns, reusable frameworks, and standardization for multi-source data integration. Ensures scalability, maintainability, and governance across ETL delivery, aligning to product roadmap and data model strategy.
Key Responsibilities
- Define reference architecture for ETL/ELT pipelines: ingestion transform serving layers.
- Establish standards for metadata/config-driven ETL, naming, error handling, and replay.
- Design scalable patterns for CDC, incremental processing, backfills, and dependency orchestration.
- Define CI/CD patterns for ETL and govern environment promotions.
- Define observability standards: logs, metrics, lineage, data quality monitoring, SLAs.
- Review designs for performance, cost, security, and operational readiness.
- Align ETL patterns with data modelling and downstream analytics/ML needs.
Must Have
- 8 to 12 years in data engineering with strong ETL architecture ownership.
- Expertise across ETL tools/frameworks (dbt + orchestration, ADF/Glue/Informatica/Talend etc.).
- Strong SQL performance and warehouse optimization knowledge.
- Airflow (or equivalent) architecture-level orchestration design.
- Python capability for framework/tooling design and automation.
- Strong knowledge of cloud data architecture (AWS/Azure/GCP).
- Delivery engineering maturity: CI/CD, versioning, release discipline, rollback strategies.
- Non-technical: strong documentation, workshop facilitation, ability to influence teams.
Good To Have
- Experience with event streaming architectures (Kafka) and lakehouse patterns.
- Exposure to data catalog/lineage tooling and governance practices.
- Familiarity with ML pipeline needs (feature readiness, time semantics).
