Data Engineer w/ Snowflake, Azure Data Factory & Dataops Experience :: 8+ years exp

Title: Data Engineer

Location: Pan India

Exp: 8+ Years

Skill:

Snowflake, Azure Data Factory, DataOps

JD:

We are looking for a skilled Data Engineer with hands-on experience in designing, building, and supporting scalable data pipelines and data products across modern cloud data platforms.

The ideal candidate should have strong experience with Azure Data Factory, Snowflake, and DataOps.live, along with a good understanding of Data Product concepts, data integration, orchestration, and engineering best practices. Power BI experience is desirable and would be considered a good-to-have skill.

Key Responsibilities:

Data Engineering & Pipeline Development

• Design, build, and maintain scalable data pipelines using Azure Data Factory.

• Develop robust ETL/ELT processes to ingest, transform, and publish data across enterprise platforms.

• Work with structured and semi-structured data, applying appropriate data modelling, validation, and quality checks.

• Write and optimise SQL for data transformation, reconciliation, and performance tuning.

Cloud Data Platform & DataOps

• Develop and support data solutions on Snowflake as a core cloud data platform.

• Use DataOps.live practices and tooling to support version-controlled, automated, and repeatable data deployments.

• Collaborate with engineering and platform teams to implement CI/CD, environment management, and release controls for data assets.

• Support monitoring, troubleshooting, and continuous improvement of data pipelines and platform processes.

Data Product Development

• Contribute to the design and delivery of reusable Data Products aligned to business and analytical needs.

• Apply data product principles such as ownership, discoverability, quality, reusability, and clear documentation.

• Work with business stakeholders, analysts, and technical teams to understand data requirements and translate them into reliable data solutions.

• Ensure data outputs are trusted, governed, and suitable for downstream reporting, analytics, and operational use cases.

Good-to-Have: Reporting & Analytics

• Familiarity with Power BI reporting, semantic models, datasets, and dashboard development.

• Ability to support reporting teams by providing well-structured, performance-optimised data models.

• Understanding of business KPIs and how data engineering outputs support analytics and decision-making.

Preferred Skills & Experience:

• Hands-on experience with Azure Data Factory, including pipeline orchestration, triggers, linked services, datasets, and monitoring.

• Strong SQL skills and experience working with cloud data platforms such as Snowflake.

• Experience with DataOps.live or similar DataOps/DevOps tooling for automated deployment and environment management.

• Understanding of Data Product concepts, metadata, governance, and documentation practices.

• Good-to-have experience in Power BI for reporting, dashboards, and data visualisation.

• Knowledge of Python or another scripting language would be advantageous.

Key Competencies:

• Strong analytical and problem-solving skills.

• Ability to build reliable, scalable, and maintainable data solutions.

• Good communication skills with the ability to work across business, data, and engineering teams.

• Attention to detail, especially around data quality, reconciliation, and documentation.

• Ability to work in an agile delivery environment and manage priorities effectively.