Position:

Senior Data Engineer

Job Description:

Job Title: Senior Data Engineer

Location : Pune/Ahmedabad/Indore

Role Summary

Build and operate scalable, reliable data pipelines on Azure. Develop batch and streaming ingestion, transform data using Databricks (PySpark/SQL), enforce data quality, and publish curated datasets for analytics and ML.

Key Responsibilities

- Design, build, and maintain ETL/ELT pipelines in Azure Data Factory and Databricks across Bronze → Silver → Gold layers.
- Implement Delta Lake best practices (ACID, schema evolution, MERGE/upsert, time travel, Z-ORDER).
- Write performant PySpark and SQL; tune jobs (partitioning, caching, join strategies).
- Create reusable components; manage code in Git; contribute to CI/CD pipelines (Azure DevOps/GitHub Actions/Jenkins).
- Apply data quality checks (Great Expectations or custom validations), monitoring, drift detection, and alerting.
- Model data for analytics (star/dimensional); publish to Synapse/Snowflake/SQL Server.
- Uphold governance and security (Purview/Unity Catalog lineage, RBAC, tagging, encryption, PII handling).
- Author documentation/runbooks; support production incidents and root-cause analysis; suggest cost/performance improvements.

Must-Have (Mandatory)

- Data Engineering & Pipelines
- Hands-on experience building production pipelines with Azure Data Factory and Databricks (PySpark/SQL).
- Working knowledge of Medallion Architecture and Delta Lake (schema evolution, ACID).

- Programming & Automation

- Strong Python (pandas/PySpark) and SQL.
- Practical Git workflow; experience integrating pipelines into CI/CD (Azure DevOps/GitHub Actions/Jenkins).
- Familiarity with packaging reusable code (e.g.,



Python wheels) and configuration-driven jobs.

- Data Modeling & Warehousing

- Solid grasp of dimensional modeling/star schemas; experience with Synapse, Snowflake, or SQL Server.

- Data Quality & Monitoring

- Implemented validation checks and alerts; exposure to drift detection and pipeline observability.

- Cloud Platforms (Azure preferred)

- ADLS Gen2, Key Vault, Databricks, ADF basics (linked services, datasets, triggers), environment promotion.

- Data Governance & Security

- Experience with metadata/lineage (Purview/Unity Catalog), RBAC, secrets management, and secure data sharing.
- Understanding of PII/PHI handling and encryption at rest/in transit.

- Collaboration

- Explicit communication, documentation discipline, Agile ways of working, and code reviews.

- - Databricks Asset Bundles (DAB) for environment promotion/infra-as-code style deployments.
- Streaming/real-time: Kafka/Event Hubs; CDC tools (e.g., Debezium, ADF/Synapse CDC).
- MLOps touchpoints: MLflow tracking/registry, feature tables, basic model-inference pipelines.
- Power BI exposure for publishing curated tables and building operational KPIs.
- DataOps practices: automated testing, data contracts, lineage-aware deployments, cost optimization on Azure.
- Certifications: Microsoft Certified — Azure Data Engineer Associate (DP-203) or equivalent.

- - 5+ years of professional experience in data engineering (or equivalent project depth).
- Bachelor’s/Master’s in CS/IT/Engineering or related field (or equivalent practical experience).

Location:

IN-GJ-Ahmedabad, India-Ognaj (eInfochips)

Time Type:

Full time

Job Category:

Engineering Services

📌 Senior Data Engineer (Indore)
🏢 Arrow
📍 Indore