About the Role
We are looking for a Senior Data Engineer to design, build, and optimize modern data platforms. You will own end-to-end data pipelines, from ingestion to analytics-ready models, ensuring data is reliable, secure, and scalable for product and business use.
Team: Data Platform / Analytics Engineering
Key Responsibilities
- Design and build batch and streaming data pipelines using Azure Data Factory, Microsoft Fabric (Data Factory, Lakehouse, Warehouse), and Azure Synapse Analytics.
- Develop large-scale data transformations using Azure Databricks / Spark (PySpark, Spark SQL) and Delta Lake.
- Build dimensional models and optimize Azure SQL, SQL Server, and Synapse for performance and cost.
- Enable analytics and self-service BI with Power BI (semantic models, DAX, dataflows, RLS).
- Implement real-time ingestion using Event Hubs, Stream Analytics, or Fabric Real-Time Intelligence.
- Set up CI/CD and Infrastructure as Code using Azure DevOps or GitHub Actions and Bicep/Terraform.
- Monitor pipelines, troubleshoot failures, and optimize cost and performance; mentor junior engineers.
Required Skills
- 5+ years of experience in data engineering with strong SQL (T-SQL) and Preferably Python/PySpark.
- Hands-on expertise in Azure Data Factory, Synapse, Databricks, and ADLS Gen2.
- Experience with Microsoft Fabric or strong readiness to work on it.
- Strong data modeling skills: star/snowflake schemas, SCDs, ETL/ELT design patterns.
- Working knowledge of Power BI and the Azure security model.
- Experience with Git, CI/CD, and agile delivery.
Good to Have
- Azure certifications: DP-203, DP-600, DP-700, AZ-900, or AZ-104.
- Experience with Delta Lake optimization, Unity Catalog, and Kafka.
- Exposure to Microsoft Purview, Azure Monitor, and Log Analytics.
- Knowledge of data governance and compliance (GDPR, DPDP, SOC 2, ISO 27001).
- Experience in SaaS or product-based companies is a plus.