Senior Data Engineer

Version 1; Bengaluru; Hybrid; INR 1,800,000 - 2,800,000; Full time

Job summary

Version 1 is seeking an experienced Data Engineer to translate business requirements into scalable data solutions. You will design, build and support Fabric-based lakehouse architectures, develop robust data pipelines using SQL, Python or PySpark, and maintain dimensional models with Power BI semantic layers.

You will also implement data quality controls, contribute to architectural decisions, and ensure security and governance across pipelines.

Qualifications

• Demonstrable hands-on experience delivering data engineering solutions using Microsoft Fabric.
• Strong SQL development, troubleshooting and performance-optimisation skills.
• Practical experience with Python or PySpark, notebooks and distributed data-processing concepts.
• Experience building and operating ETL/ELT pipelines and integrating cloud, on-premises or third-party data sources.
• Experience with Fabric lakehouse and warehouse patterns, orchestration, OneLake concepts and Power BI semantic models, including Direct Lake where appropriate.
• Experience with data warehouses, data lakes and Azure data services such as Azure Data Lake Storage and Azure Data Factory.
• Strong knowledge of dimensional modelling, analytical structures and data-modelling trade-offs.
• Experience implementing unit, integration, reconciliation and regression testing for data solutions.
• Experience with Git, pull requests, source control, CI/CD and automated deployment

Responsibilities

• Translate business requirements into technical designs, delivery estimates, implementation tasks and acceptance criteria.
• Design, build and support Microsoft Fabric solutions using appropriate lakehouse, warehouse, orchestration and semantic-modelling patterns.
• Develop robust ingestion, ETL/ELT and integration pipelines using SQL, Python or PySpark as appropriate.
• Design and maintain dimensional and analytical data models, including star schemas, facts, dimensions and Power BI semantic models.
• Implement automated data-quality, validation, reconciliation and schema-change controls.
• Contribute to architecture decisions and lead detailed design sessions for assigned components or workstreams.
• Apply security and governance controls including least privilege, classification, lineage, metadata, retention and auditability.
• Use source control, peer review, automated testing, CI/CD and repeatable deployment practices.
• Create and maintain technical documentation including data flows, architecture views, configuration, support procedures and runbooks.
• Estimate and plan engineering work, manage dependencies and communicate delivery risks within Agile teams.
• Support testing, release, monitoring, troubleshooting, incident investigation and continuous improvement in production.
• Mentor junior engineers, review technical work and promote reusable patterns and engineering standards.
• Communicate solution options, progress, risks and recommendations to technical and non-technical stakeholders.

Skills

SQL development

Python/PySpark

Data engineering

Performance optimisation

Git & CI/CD

Fabric lakehouse

Tools

Microsoft Fabric

Power BI

Azure Data Factory

Azure Data Lake Storage

OneLake

Job description

• Translate business requirements into technical designs, delivery estimates, implementation tasks and acceptance criteria.


• Design, build and support Microsoft Fabric solutions using appropriate lakehouse, warehouse, orchestration and semantic-modelling patterns.


• Develop robust ingestion, ETL/ELT and integration pipelines using SQL, Python or PySpark as appropriate.


• Design and maintain dimensional and analytical data models, including star schemas, facts, dimensions and Power BI semantic models.


• Implement automated data-quality, validation, reconciliation and schema-change controls.


• Contribute to architecture decisions and lead detailed design sessions for assigned components or workstreams.


• Apply security and governance controls including least privilege, classification, lineage, metadata, retention and auditability.


• Use source control, peer review, automated testing, CI/CD and repeatable deployment practices.


• Create and maintain technical documentation including data flows, architecture views, configuration, support procedures and runbooks.


• Estimate and plan engineering work, manage dependencies and communicate delivery risks within Agile teams.


• Support testing, release, monitoring, troubleshooting, incident investigation and continuous improvement in production.


• Mentor junior engineers, review technical work and promote reusable patterns and engineering standards.


• Communicate solution options, progress, risks and recommendations to technical and non-technical stakeholders.

Qualifications

Essential

• Demonstrable hands-on experience delivering data engineering solutions using Microsoft Fabric.


• Strong SQL development, troubleshooting and performance-optimisation skills.


• Practical experience with Python or PySpark, notebooks and distributed data-processing concepts.


• Experience building and operating ETL/ELT pipelines and integrating cloud, on-premises or third-party data sources.


• Experience with Fabric lakehouse and warehouse patterns, orchestration, OneLake concepts and Power BI semantic models, including Direct Lake where appropriate.


• Experience with data warehouses, data lakes and Azure data services such as Azure Data Lake Storage and Azure Data Factory.


• Strong knowledge of dimensional modelling, analytical structures and data-modelling trade-offs.


• Experience implementing unit, integration, reconciliation and regression testing for data solutions.


• Experience with Git, pull requests, source control, CI/CD and automated deploymen