Lead Data Engineer - Azure

Role Overview

We are seeking a skilled Azure Data Engineer with 5+ years of experience in designing, developing, and maintaining modern data pipelines and data integration solutions using Azure services. The ideal candidate should have strong expertise in Azure Data Factory (ADF), Azure Databricks, Azure Synapse, and Azure Data Lake Storage (ADLS). You will work closely with business analysts, architects, and data scientists to deliver reliable and scalable data solutions that power analytics and business intelligence platforms.

Key Responsibilities

Data Ingestion & Integration

• Design, build, and maintain data pipelines using Azure Data Factory for batch and incremental data ingestion.
• Connect to various data sources (SQL Server, REST APIs, CSV, JSON, SAP, etc.) and integrate into the Azure ecosystem.
• Develop metadata-driven and parameterized pipelines to improve reusability.
• Implement data validation, error handling, and logging frameworks in ADF.

Data Transformation & Processing

• Use Azure Databricks (PySpark) for data cleansing, transformation, and enrichment.
• Optimize Spark jobs for performance and cost efficiency.
• Implement ETL/ELT workflows with Delta Lake and Medallion (Bronze, Silver, Gold) architecture.

Data Storage & Modeling

• Work with Azure Data Lake Storage Gen2 for raw and curated data zones.
• Develop data models in Azure Synapse Analytics / SQL Server for reporting and analytics.
• Implement partitioning, indexing, and performance tuning strategies.

Deployment & DevOps

• Implement CI/CD pipelines using Azure DevOps or GitHub Actions for data workflows.
• Collaborate with architects to automate deployments and version control using Git.

Security & Governance

• Manage data access using Azure RBAC, Managed Identities, and Key Vault.
• Ensure data security, compliance, and privacy as per organizational standards.

Collaboration

• Work with data analysts, BI developers, and business users to define data requirements.
• Participate in code reviews and adhere to best practices in data engineering.

Technical Skills Required

• Azure Services: Azure Data Factory, Azure Databricks, Azure Synapse, ADLS Gen2, Azure SQL Database
• Programming: Python (PySpark), SQL, Spark SQL
• Data Modeling: Star/Snowflake schema, Dimensional modeling
• Source Systems: SQL Server, Oracle, SAP, Flat Files (CSV, JSON, XML), REST APIs
• Version Control & CI/CD: Git, Azure DevOps
• Scheduling & Monitoring: ADF triggers, Databricks jobs, Log Analytics
• Security: Managed Identity, Key Vault, Access Control
• Preferred: Power BI basics, exposure to DataBricks Delta Live Tables or Synapse Pipelines

Soft Skills

• Strong analytical and problem-solving skills.
• Good communication and collaboration abilities.
• Ability to work in agile/scrum environments.
• Self-driven and proactive in identifying process improvements.

Educational Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Azure Data Engineer Associate (DP-203) certification preferred.

Example Project Responsibilities

• Design and implement end-to-end data ingestion from on-prem SQL Server to Azure Data Lake using ADF.
• Build Databricks notebooks for data cleansing and transformations using PySpark.
• Implement Delta Lake tables and load curated data into Synapse for reporting.
• Collaborate with BI teams to publish Power BI dashboards on top of Synapse datasets.

Optional (Good To Have)

• Experience with Real-time data processing (Event Hub / Stream Analytics).
• Knowledge of Infrastructure as Code (IaC) using Terraform or ARM templates.
• Familiarity with data quality and data catalog tools (Purview).

Key skills/competency

• Azure Data Factory
• Azure Databricks
• Azure Synapse
• Azure Data Lake Storage (ADLS)
• PySpark
• SQL
• Data Modeling
• ETL/ELT
• CI/CD
• Data Engineering