Azure Data Engineer

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About the Role

Senior Data Engineer

Key Responsibilities

• Design and develop ETL/ELT pipelines using

  Azure Data Factory, Databricks, and Synapse

• Build batch and real-time data ingestion pipelines (APIs, SaaS, on-prem, streaming)
• Implement data models (star schema, snowflake, data vault)
• Manage data lakes using

  ADLS Gen2

• Ensure data quality, governance, security, and compliance (RBAC, AAD, Purview)
• Implement CI/CD pipelines using

  Azure DevOps / GitHub Actions

• Optimize Azure cost, performance, and scalability
• Mentor junior engineers and participate in architecture decisions
• Work cross-functionally with BI, AI, and product teams

Mandatory Skills

Azure Data Factory (ADF)

Azure Databricks (PySpark, Delta Lake)

Azure Synapse Analytics (SQL Pools)

Python / PySpark / SQL

ADLS Gen2

Event Hubs / Kafka / Stream Analytics

CI/CD, Git, and DevOps practices

✔ Strong understanding of data warehousing & dimensional modeling

Good to Have

✔ Azure Purview, Power BI integration

✔ API-based data ingestion

✔ Exposure to ML data pipelines / feature stores

✔ Terraform / ARM / Bicep (IaC)

Important Note (Please Read Before Applying)

Do NOT apply if:

• You have less than

  8 years

  of total data engineering experience
• You lack hands-on experience with

  Azure data services

• You do not have strong

  Python / PySpark / SQL

  expertise

Apply ONLY if you meet all mandatory requirements.

Irrelevant or mismatched profiles will not be processed.