Data Engg with Databricks+ PySpark -Sr Technical Lead-Data Engg

Birlasoft ( India ) Limited; Pune District; On-site; INR 1,200,000 - 1,500,000; Full time

Job summary

Birlasoft ( India ) Limited is looking for a Senior Azure Data Engineer / Sr. Technical Lead to drive large-scale data engineering solutions using Azure Databricks and PySpark. The ideal candidate will showcase strong technical leadership and hands-on skills necessary to architect enterprise-scale data solutions.

Responsibilities include leading design initiatives, building ELT/ETL pipelines, and ensuring data quality and governance. This role demands collaboration with cross-functional teams to adapt business requirements into technical solutions.

Qualifications

• Extensive experience in data engineering with Azure Databricks and PySpark.
• Strong technical leadership skills to mentor and guide teams.
• Experience in architecting and deploying enterprise-scale data solutions.

Responsibilities

• Lead the design and deployment of large-scale data engineering solutions.
• Build and maintain scalable ELT/ETL pipelines.
• Collaborate with stakeholders to develop technical solutions.

Skills

Azure Databricks

PySpark

ADF (Azure Data Factory)

SQL

Data Governance

Job description

Title: Data Engg with Databricks+ PySpark -Sr Technical Lead-Data Engg

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.