Job Purpose

Responsible for designing, building, and optimizing scalable data infrastructure and pipelines on Microsoft Fabric and Snowflake that support the organization's data engineering, analytics, and AI capabilities. Serves as a senior technical contributor, driving engineering excellence, ensuring reliable and high-performing data solutions, and providing guidance to junior engineers.

Key Result Responsibilities

Design and deliver complex, scalable data pipelines and infrastructure components end-to-end, from requirements through to production, on Fabric and Snowflake

Own the technical design and implementation of data models across relational and lakehouse architectures — leveraging Fabric OneLake/Lakehouse and Snowflake — to support analytics and ML workloads

Architect and optimize data flows across Microsoft Fabric and Snowflake, ensuring performance, cost-efficiency, and reliability

Build and maintain robust orchestration workflows using tools such as Fabric Data Factory pipelines and Snowflake Tasks/Streams

Define and implement data quality frameworks — validation rules, automated testing, monitoring, and alerting — across assigned pipeline domains in Fabric and Snowflake

Collaborate closely with Data Scientists and Analytics Engineers to ensure data infrastructure meets downstream consumption requirements

Contribute to architectural reviews and platform decisions, providing well-reasoned technical input and trade-off analysis

Lead code reviews and enforce engineering best practices, documentation standards, and security and governance requirements

Mentor Associate and mid-level Data Engineers, providing technical guidance and supporting their professional development

Proactively identify platform improvements, technical debt,



and opportunities to modernize the data stack

Qualifications (Academic, Training, Languages)

Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Technology, or a related field.

Proven experience working with large-scale cloud data platforms in a skilled setting, specifically Microsoft Fabric and Snowflake

ITIL Certification is an advantage but not mandatory

Fluent in English language.

Expert-level SQL and strong Python skills, with hands-on experience in Snowpark; working knowledge of Spark, Scala, or Java is a plus

Deep hands-on experience with Microsoft Fabric components (e.g., Data Factory (Fabric), Lakehouse, Warehouse, OneLake) and Snowflake (e.g., Snowpark, Streams, Tasks, external tables)

Advanced knowledge of data orchestration tools (e.g., Fabric Data Factory pipelines) and CI/CD practices for data pipelines in Snowflake and Fabric

Solid understanding of dimensional and data vault modelling techniques and lakehouse architecture patterns, particularly within the Fabric OneLake and Snowflake ecosystems

Experience with streaming and batch processing frameworks (e.g., Azure Event Hubs, Snowflake Snowpipe/Streaming)

Strong grasp of data governance, data quality frameworks, and metadata management practices (e.g., Microsoft Purview, Snowflake governance features)

Ability to communicate complex technical designs clearly and mentor less experienced engineers effectively

Strong experience with Snowflake and Microsoft Fabric Warehouse for data warehousing, including performance tuning and access control

Work Experience

~ With 6-8 years of progressive hands-on experience in data engineering, with a demonstrable track record of delivering production-grade data infrastructure on Microsoft Fabric and/or Snowflake

📌 Senior Data Engineer - AI & Data (Pune)
🏢 Air Arabia
📍 Pune