Project Role : Custom Software Engineer

Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

Must have skills : Microsoft Azure Databricks

Good to have skills : NA

Minimum 7.5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Job Summary

We are seeking an experienced Data Engineering Lead with deep expertise in Azure Data Services, Azure Synapse Analytics, and Azure Databricks to design, build, and lead the development of scalable, end-to-end data pipelines. The role involves owning the data architecture from source ingestion to consumption layers, ensuring high performance, reliability, and data quality while mentoring a team of data engineers.

Key Responsibilities :

Lead the design, development, and optimization of end-to-end data pipelines from multiple source systems to analytics and reporting layers
Architect and implement modern data platforms on Azure using:

Azure Data Factory / Synapse Pipelines

Azure Synapse Analytics (Dedicated & Serverless SQL pools)

Azure Databricks (Delta Lake, Spark)

Azure Data Lake Storage (ADLS Gen2)

Define and enforce data modeling standards (bronze/silver/gold layers, star/snowflake schemas)
Ensure efficient data ingestion, transformation, and orchestration for batch and near-real-time workloads
Optimize data pipelines for performance, scalability, cost, and reliability
Collaborate with business stakeholders, architects, analysts, and data scientists to align data solutions with business needs
Lead and mentor a team of data engineers, conducting code reviews and enforcing best practices
Implement data governance, security, and compliance (RBAC, data masking, encryption)
Drive CI/CD automation for data pipelines using Azure DevOps or GitHub Actions
Monitor, troubleshoot, and resolve pipeline failures and performance issues
Participate in architecture reviews and contribute to long-term data strategy

Required Skills & Qualifications

8+ years of experience in data engineering, with proven leadership experience
Strong hands-on expertise in Azure Data Services
Extensive experience with: Azure Synapse Analytics, Azure Databricks (Apache Spark, Delta Lake), Azure Data Factory / Synapse Pipelines
Proven experience building end-to-end data pipelines from source systems (RDBMS, APIs, files, streaming) to consumption layers (BI, analytics, ML)
Strong SQL and Python/Scala skills
Experience with data warehousing and lakehouse architectures
Solid understanding of ETL/ELT patterns, data partitioning, and performance tuning
Experience with CI/CD, version control, and DevOps practices
Strong communication and stakeholder management skills

Experience: 8 12+ years (with 3 5 years in a lead role)

Preferred / Nice-to-Have

Azure certifications (e.g., Azure Data Engineer Associate, Azure Solutions Architect)
Experience with Power BI or other BI tools
Exposure to real-time/streaming data (Event Hub, Kafka, Structured Streaming)