Data Engg With Databricks PySpark -Sr Technical Lead-Data Engg

Birlasoft; Pune District; On-site; INR 3,000,000 - 5,000,000; Full time

Job summary

Birlasoft is seeking a seasoned Senior Azure Data Engineer / Sr. Technical Lead to architect and deliver enterprise-scale data solutions on Azure. You will lead complex data initiatives, mentor teams, and collaborate with cross-functional stakeholders to build a scalable data ecosystem.

You will design MDW/Lakehouse architectures, optimize performance and security, and drive best practices across the data engineering lifecycle, including CI/CD integration.

Qualifications

• Seasoned data engineer with strong leadership and mentoring abilities.
• Experience delivering enterprise-scale data solutions on Azure.
• Ability to design architecture and govern data platforms.

Responsibilities

• Lead the design, development, and deployment of large-scale data solutions on Azure Databricks, PySpark, ADF, and SQL.
• Architect end-to-end MDW and Lakehouse solutions with security and cost optimization.
• Provide technical leadership across the project lifecycle and mentor engineers.

Skills

Technical leadership

Mentoring

Stakeholder collaboration

Architectural design

Tools

Azure Databricks

PySpark

ADF

SQL

Delta Lake

Job description

Job Description:

Area(s) of responsibility

Role Summary

We are seeking a seasoned Senior Azure Data Engineer / Sr. Technical Lead with extensive expertise in Azure Databricks, PySpark, ADF, SQL, and modern data engineering practices. This role requires strong technical leadership, hands on engineering capabilities, and the ability to design, architect, and deliver enterprise-scale data solutions. The ideal candidate will lead complex data initiatives, mentor engineering teams, and collaborate with cross-functional stakeholders to build a robust and scalable data ecosystem on Azure.

Key Responsibilities

1. Solution Architecture & Technical Leadership
   Lead the design, development, and deployment of large-scale data engineering solutions using Azure Databricks, PySpark, SQL, ADF, and Azure Data Lake.
   Architect end-to-end Modern Data Warehouse (MDW) and Lakehouse solutions, ensuring scalability, performance, security, and cost optimization.
   Define technical standards, coding best practices, reusable frameworks, and architectural guidelines for engineering teams.
   Provide technical leadership across the project lifecycle—requirements analysis, solution blueprinting, estimation, development, and deployment.
2. Data Pipeline Engineering
   Build, optimize, and maintain scalable, high performance ELT/ETL pipelines to process large volumes of structured and unstructured data.
   Set up complex data ingestion frameworks, enabling seamless integration with on-premise systems, cloud services, APIs, and third-party sources.
   Ensure high availability, data reliability, and error-resilient orchestration workflows in Azure Data Factory.
3. Azure Databricks & PySpark Expertise
   Design and implement advanced transformation logic using PySpark on Databricks, ensuring efficient data processing and code modularity.
   Utilize Delta Lake capabilities—ACID transactions, schema evolution, versioning, time travel—to manage enterprise-grade datasets.
   Perform cluster-level tuning, optimization of shuffle operations, caching, partitioning, and job parallelization.
   Manage Databricks job pipelines, notebooks, clusters, job scheduling, and integration with CI/CD pipelines.
4. Data Governance, Quality & Documentation
   Implement data quality frameworks covering validation, reconciliation, error handling, and metadata management.
   Enforce best practices for security, access control, encryption, data lineage, and auditability.
   Prepare and maintain detailed documentation: technical specification documents, interface designs, architecture diagrams, and operational runbooks.
5. Stakeholder Collaboration & Team Leadership
   Collaborate with BI, analytics, business teams, and architects to convert business requirements into scalable technical solutions.
   Lead code reviews, provide mentoring and technical guidance to junior and mid-level engineers.
   Work closely with Scrum Masters and Product Owners within an Agile delivery model.