Job Title: Azure Data Engineer
Location: Pune (Work from Office)
Experience: 3–5 Years
Role Overview
We are looking for a motivated Azure Data Engineer with 3–5 years of experience to design,
build, and optimize scalable data platforms on Microsoft Azure.
The ideal candidate will have strong hands-on experience in Azure Databricks, Azure Data
Factory, and modern data lake architectures, along with a solid
understanding of data engineering principles and data warehouse design.
The role requires working on data pipeline development, data platform architecture, and
large-scale data processing while collaborating with internal teams and clients to deliver
reliable data solutions.
We are looking for a dynamic, self-driven professional who can take ownership of data
engineering tasks and contribute to modern cloud data platform implementations.
Key Responsibilities – Data Pipeline Development
- Design and develop scalable ETL/ELT pipelines using Azure data services
- Build and orchestrate workflows using Azure Data Factory
- Develop large-scale data processing solutions using Azure Databricks and PySpark
- Implement ingestion pipelines for structured, semi-structured, and unstructured datasets
- Store and manage large datasets using Azure Data Lake Storage (ADLS)
- Develop optimized data transformations using Python, PySpark, and SQL
Databricks and Lakehouse Development
- Develop scalable data processing pipelines using Azure Databricks
- Implement Delta Lake architecture for reliable data storage and processing
- Manage Unity Catalog for centralized data governance and access control
- Optimize Spark jobs, partitioning strategies, and cluster performance
- Implement time travel and versioned data management using Delta Lake
- Design Lakehouse architectures for analytics and reporting workloads
Data Platform and Architecture
- Participate in modern data platform design and architecture discussions
- Implement data lake and data warehouse solutions on Azure
- Contribute to data migration and modernization initiatives from legacy platforms to cloud
- Implement best practices for data governance, metadata management, and data quality
Data Modeling and Engineering Concepts
Strong understanding of:
- ETL and ELT architecture
- Data warehouse design (Star Schema and Snowflake Schema)
- Slowly Changing Dimensions (SCD)
- Normalization and Denormalization
- Handling late arriving data
- Time travel and versioned data
- Data quality frameworks
- Data governance concepts
DevOps and Data Operations
- Implement CI/CD pipelines using Azure DevOps
- Use Git for version control and collaborative development
- Monitor and optimize pipeline performance and reliability
- Implement logging, monitoring, and alerting for data pipelines
Client Interaction
- Work with clients and business stakeholders to gather and clarify data requirements
- Translate business requirements into scalable data engineering solutions
- Participate in architecture discussions and solution design sessions
- Support delivery teams with technical guidance on data platform implementations
Required Technical Skills
Azure Data Platform
- Azure Data Factory
- Azure Databricks
- Azure Data Lake Storage (ADLS)
- Azure SQL / SQL Server
- Logic Apps
Programming and Processing
Data Platforms
- Data Lake Architecture
- Data Warehouse Concepts
- Delta Lake
- Unity Catalog
DevOps
- Azure DevOps
- CI/CD pipelines
- Git
Technologies
Azure Databricks, Azure Data Factory, Azure Data Lake Storage (ADLS), Azure SQL, Logic
Apps, Python, PySpark, SQL, Delta Lake,
Unity Catalog, Azure DevOps, Git, Data Warehousing, ETL/ELT, Microsoft Fabric, Lakehouse
Architecture, OneLake
Preferred Skills
- Knowledge of Microsoft Fabric ecosystem
- Experience with Fabric Lakehouse
- Understanding of OneLake unified storage
- Exposure to Fabric Data Factory and Fabric notebooks
- Experience in data migration projects (on-premise to cloud or cross-platform)
- Experience optimizing large-scale Spark workloads
Soft Skills
- Strong analytical and problem-solving mindset
- Self-starter with proactive attitude
- Ability to work in dynamic and fast-paced environments
- Strong communication and client-facing skills
- Ability to take ownership and deliver end-to-end solutions
Experience
- 3–5 years of experience in Data Engineering
- At least 2+ years working with Azure data platforms
- Hands-on experience with Azure Databricks and large-scale data processing
Education
Bachelor’s or Master’s degree in Computer Science, Information Technology, Data
Engineering, or related field
Send your CV to [email protected]
Subject: Application – Azure Data Enginee
Work Location: In person
