Birlasoft

2 weeks ago

Azure Data Engineer + Databricks --Technical Lead-Data Engg

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Design, build, and optimize Azure-based data platforms and analytical solutions. Own end-to-end data engineering architecture using Azure Data Factory, Azure Databricks, PySpark, and SQL, including scalable lakehouse and modern data warehouse implementations. Develop robust high-throughput ELT/ETL pipelines for multi-source ingestion and complex transformations, implement Delta Lake features, and tune performance across clusters, jobs, and notebooks.

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Architect end-to-end data engineering solutions using Azure Data Factory, Azure Databricks, PySpark, SQL, and other Azure services.
•Design and implement scalable, secure modern data warehouse (MDW) and lakehouse solutions using Azure Data Lake Storage and Databricks.
•Build and optimize robust, high-throughput ELT/ETL pipelines for structured, semi-structured, and unstructured data ingestion and transformation.
•Develop orchestration workflows in ADF, including pipelines, triggers, linked services, integration runtimes, and parameterized datasets.
•Implement and tune Databricks transformations with PySpark and Delta Lake features, and collaborate on managing clusters, jobs, notebooks, and CI/CD integrations.

Key Requirements

•7–10 years of experience in data engineering with strong hands-on exposure to the Azure data ecosystem.
•At least 2 years of real project experience with Azure Databricks (not POCs).
•At least 2 years of hands-on experience building data pipelines using Azure Data Factory (ADF).
•At least 2 years of experience developing PySpark-based transformations in Databricks.
•Experience with Azure Data Lake Storage (ADLS Gen2), data partitioning strategies, and file formats like Parquet/Delta/JSON.

Experience:7-10 years

Skills:Data engineeringSolution designPerformance tuningData pipeline developmentEnterprise architecture

Tech Stack:AzureAzure DatabricksPySparkAzure Data FactorySQLAzure Data Lake Storage (ADLS Gen2)Delta LakeELTETLParquetJSONCI/CDData Warehouse (MDW)LakehouseACID transactionsSchema evolutionTime travelCachingPartitioningShuffle operations

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

2 weeks ago

Azure Data Engineer + Databricks --Technical Lead-Data Engg

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: Pune

Workplace: Onsite

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Architect end-to-end data engineering solutions using Azure Data Factory, Azure Databricks, PySpark, SQL, and other Azure services.
•Design and implement scalable, secure modern data warehouse (MDW) and lakehouse solutions using Azure Data Lake Storage and Databricks.
•Build and optimize robust, high-throughput ELT/ETL pipelines for structured, semi-structured, and unstructured data ingestion and transformation.
•Develop orchestration workflows in ADF, including pipelines, triggers, linked services, integration runtimes, and parameterized datasets.
•Implement and tune Databricks transformations with PySpark and Delta Lake features, and collaborate on managing clusters, jobs, notebooks, and CI/CD integrations.

Key Requirements

•7–10 years of experience in data engineering with strong hands-on exposure to the Azure data ecosystem.
•At least 2 years of real project experience with Azure Databricks (not POCs).
•At least 2 years of hands-on experience building data pipelines using Azure Data Factory (ADF).
•At least 2 years of experience developing PySpark-based transformations in Databricks.
•Experience with Azure Data Lake Storage (ADLS Gen2), data partitioning strategies, and file formats like Parquet/Delta/JSON.

Experience:7-10 years

Skills:Data engineeringSolution designPerformance tuningData pipeline developmentEnterprise architecture

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