Azure Databricks + PySpark -Sr Technical Lead-Data Engg

Birlasoft ( India ) Limited; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Birlasoft ( India ) Limited is seeking a Senior Azure Data Engineer to lead complex data initiatives. The role requires extensive expertise in Azure Databricks, PySpark, and data engineering practices.

Responsibilities include designing solutions, building data pipelines, and collaborating with cross-functional teams. Successful candidates will demonstrate strong technical leadership and hands-on engineering capabilities. This position is vital to architecting enterprise-scale data solutions in a dynamic environment.

Qualifications

• Strong technical leadership capabilities with experience in Azure data services.
• Expertise in building and maintaining scalable data pipelines.
• Proficiency in data governance and quality practices.

Responsibilities

• Lead design and development of data engineering solutions.
• Build and maintain ELT/ETL pipelines for data processing.
• Collaborate with stakeholders to ensure alignment on technical solutions.

Skills

Azure Databricks

PySpark

Azure Data Factory (ADF)

SQL

Data Pipeline Engineering

Tools

Azure Data Lake

Delta Lake

Job description

Location: INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI

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.