Data Engineer - Snowflake + Azure - IND

Role: Data Engineer (Snowflake + Azure)
Location: India, Remote
Experience: 7+ yrs
Job Type: Contract 6 months+ possible extension

Key Responsibilities

• Design, build and maintain ELT pipelines that ingest data into Snowflake from Azure Synapse, on-premises SQL Server and enterprise applications (e.g. Dynamics 365, ERP and clinical/rostering platforms as they are onboarded).
• Develop and maintain dbt models (staging, intermediate and mart layers) that form national data model, applying sound dimensional modelling practices and consistent business definitions across the merged entities.
• Support the migration and consolidation of existing Azure Synapse and SQL Server workloads into Snowflake, including refactoring logic, reconciling outputs and validating data against legacy reports.
• Build and schedule data orchestration using Azure Data Factory and/or native Snowflake and dbt scheduling.
• Deliver curated, well-documented datasets and semantic models that feed Power BI reporting across residential aged care, home and community services, retirement living and corporate functions.
• Prepare trusted, AI-ready data to support AI use cases on Azure OpenAI within its own tenancy, in line with data sovereignty, privacy and responsible AI principles.
• Implement data quality tests, documentation and lineage in dbt, and contribute to data governance, role-based access control and Snowflake performance and cost optimisation.
• Follow Git-based version control, code review and CI/CD practices for all data assets.
• Collaborate with onshore data, analytics and architecture teams across time zones, participate in agile ceremonies and maintain clear technical documentation and handover material.

Skill Summary

• Data Platforms: Snowflake (warehouse design, RBAC, performance tuning, cost management); Azure Synapse Analytics
• Transformation & Modelling: dbt (Core and/or Cloud); dimensional modelling (Kimball); enterprise data model design
• Languages: Advanced SQL (T-SQL and Snowflake SQL); Python desirable
• Integration & Orchestration: Azure Data Factory; dbt scheduling; Snowflake tasks and streams
• Cloud: Microsoft Azure (storage, networking and security fundamentals)
• Reporting & BI: Power BI datasets and semantic models
• DevOps: Git, CI/CD (Azure DevOps or GitHub Actions)
• Security & Governance: Data quality frameworks, lineage, access controls, handling of sensitive personal and health-related data