Databricks - Sr Technical Lead-Data Engg - Birlasoft

OpenTalent; Maharashtra; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

OpenTalent is seeking a Databricks - Sr Technical Lead-Data Engg to architect and deliver modern data platforms on Azure. You will lead Databricks and PySpark transformations, manage data pipelines, and implement governance with Unity Catalog across on-prem and cloud sources.

Responsibilities include building ingestion frameworks, optimizing ETL/ELT, and ensuring scalable, reusable data models with conformed dimensions and robust data quality checks.

Qualifications

• Strong hands on expertise in Databricks, PySpark, ADF, and SQL.
• Experience building enterprise-grade data pipelines and analytic solutions on Azure.

Responsibilities

• Data Engineering Execution: Build and maintain ingestion frameworks (ADF / Databricks / Spark); implement Bronze -> Silver transformations; design data quality checks and schema validation.
• Databricks & PySpark Engineering: Develop scalable PySpark transformations; apply Delta Lake features; optimize performance; manage Databricks clusters, jobs, and CI/CD integration.
• Data Governance & Quality: Implement data quality checks and validation in Unity Catalog; enforce naming conventions and metadata policies; manage access controls.

Skills

Databricks

PySpark

ADF

SQL

Tools

Delta Lake

Unity Catalog

Databricks Genie

Job description

Country/Region: IN

Location: INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI

Title: Databricks - Sr Technical Lead-Data Engg

Role Summary

We are looking for a highly skilled Databricks Data Engineer with strong hands on expertise in Databricks, PySpark, ADF, and SQL. The candidate will be responsible for architecting, developing, and optimizing modern data platforms and analytical solutions on Azure. The role requires strong experience building enterprise-grade data pipelines, enabling ingestion from diverse sources, implementing complex transformations, and supporting scalable analytics initiatives.

Key Responsibilities

1. Data Engineering Execution

• Build and maintain ingestion frameworks (ADF / Databricks / Spark)
• Implement Bronze -> Silver transformations aligned to architecture
• Architect data quality checks, schema validation, and contract rules
• Build and optimize robust, high-throughput ELT/ETL pipelines, enabling ingestion, transformation, and curation of structured, semi structured, and unstructured data.
• Integrate data from multiple on premise and cloud based systems, APIs, and third-party sources.
• Implement complex transformations using PySpark, ensuring performance efficiency and code modularity.
• Build orchestration workflows in ADF, including pipelines, triggers, linked services, integration runtimes, and parameterized datasets.
• Familiar with using Databricks Genie.
• Build: Dimensional models (star/snowflake schemas), Fact tables, dimensions, surrogate keys, SCD handling
• Translate Silver datasets into: Analytics-ready models, Consistent KPI definitions and business logic
• Ensure: Consistency across domains (common dimensions, conformed models), Reusability and scalability of models

2. Databricks & PySpark Engineering

• Develop scalable transformation scripts using PySpark on Databricks, applying advanced optimizations like caching, partitioning, and Delta Lake capabilities.
• Implement Delta Lake features—ACID transactions, schema enforcement, schema evolution, and time travel—across the data lifecycle.
• Perform performance tuning, handling bottlenecks related to cluster configuration, shuffle operations, joins, and parallelization.
• Collaborate with platform teams to manage Databricks clusters, jobs, notebooks, and CI/CD integrations.

3. Data Governance & Quality

• Implement data quality checks, audit mechanisms, and validation frameworks to ensure data accuracy and consistency in Unity Catalog.
• Enforce: Unity Catalog standards; naming conventions, metadata policies; access controls (RBAC/ABAC).