Birlasoft

1 month ago

Data Engg with Databricks - Technical Lead-Data Engg (INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI, IN)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Seeking an Azure Data Engineer to architect and optimize enterprise-grade data platforms on Azure, with hands-on expertise in Azure Databricks, PySpark, ADF, and SQL. You’ll design end-to-end data solutions, build high-throughput ELT/ETL pipelines, implement Delta Lake, govern data quality and security, and mentor junior engineers while collaborating with BI/analytical teams to deliver production-ready data capabilities.

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Administration & Executive Assistance

Key Responsibilities

•Design end-to-end data engineering solutions using Azure Data Factory, Azure Databricks, PySpark, SQL, and other Azure-native services; architect scalable MDW/Lakehouse solutions leveraging Azure Data Lake Storage and Databricks; develop data models and reusable frameworks; participate in requirements and feasibility assessments.
•Build and optimize robust ELT/ETL pipelines, ingesting, transforming, and curating structured, semi-structured, and unstructured data from diverse sources, including on-prem and cloud systems and APIs.
•Develop scalable transformation scripts with PySpark on Databricks; apply optimizations like caching, partitioning, and Delta Lake features (ACID, schema enforcement/evolution, time travel); manage Databricks clusters, jobs, notebooks, and CI/CD integrations.
•Implement data governance and quality checks, audit mechanisms, and validation frameworks to ensure data accuracy and security; enforce encryption, access control, and data lifecycle management; create technical docs and data flow diagrams.
•Collaborate with BI/analytics teams and cross-functional engineering teams to understand data requirements and deliver production-ready solutions; provide mentoring to junior engineers when required.

Key Requirements

•Must have hands-on expertise in Azure Databricks, PySpark, Azure Data Factory (ADF), and SQL
•Experience designing and implementing end-to-end data pipelines (ELT/ETL) across on-premises and cloud sources
•Proficiency in building scalable Modern Data Warehouse (MDW) and Lakehouse solutions using Azure Data Lake Storage and Databricks
•Ability to develop scalable data models, integration patterns, and reusable frameworks aligned with enterprise standards
•Knowledge of data governance, quality checks, encryption, access control, and data lifecycle management

Experience:Data engineeringCloudAzure

Skills:CommunicationLeadershipMentoringProblem-solvingTeamwork

Languages:English

Tech Stack:Azure DatabricksPySparkADFSQLDelta LakeAzure Data Lake StorageDatabricks

Company Brief

Birlasoft

Birlasoft is a global IT services and digital solutions provider delivering consulting, enterprise applications, cloud, and infrastructure services to enterprises across industries, helping accelerate digital transformation and business modernization.

Industry: Professional Services

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Noida, India

Website LinkedIn

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Birlasoft

1 month ago

Data Engg with Databricks - Technical Lead-Data Engg (INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI, IN)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 11 hours agoStatus: Live

Job Summary

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: Administration & Executive Assistance

Key Responsibilities

•Design end-to-end data engineering solutions using Azure Data Factory, Azure Databricks, PySpark, SQL, and other Azure-native services; architect scalable MDW/Lakehouse solutions leveraging Azure Data Lake Storage and Databricks; develop data models and reusable frameworks; participate in requirements and feasibility assessments.
•Build and optimize robust ELT/ETL pipelines, ingesting, transforming, and curating structured, semi-structured, and unstructured data from diverse sources, including on-prem and cloud systems and APIs.
•Develop scalable transformation scripts with PySpark on Databricks; apply optimizations like caching, partitioning, and Delta Lake features (ACID, schema enforcement/evolution, time travel); manage Databricks clusters, jobs, notebooks, and CI/CD integrations.
•Implement data governance and quality checks, audit mechanisms, and validation frameworks to ensure data accuracy and security; enforce encryption, access control, and data lifecycle management; create technical docs and data flow diagrams.
•Collaborate with BI/analytics teams and cross-functional engineering teams to understand data requirements and deliver production-ready solutions; provide mentoring to junior engineers when required.

Key Requirements

•Must have hands-on expertise in Azure Databricks, PySpark, Azure Data Factory (ADF), and SQL
•Experience designing and implementing end-to-end data pipelines (ELT/ETL) across on-premises and cloud sources
•Proficiency in building scalable Modern Data Warehouse (MDW) and Lakehouse solutions using Azure Data Lake Storage and Databricks
•Ability to develop scalable data models, integration patterns, and reusable frameworks aligned with enterprise standards
•Knowledge of data governance, quality checks, encryption, access control, and data lifecycle management

Experience:Data engineeringCloudAzure

Skills:CommunicationLeadershipMentoringProblem-solvingTeamwork

Languages:English

Tech Stack:Azure DatabricksPySparkADFSQLDelta LakeAzure Data Lake StorageDatabricks

Company Brief

Birlasoft

Industry: Professional Services

Company Size: Enterprise (1,001+ employees)

Revenue: USD 500M to 1B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Noida, India

Website LinkedIn