Sr. Data Analytics Engineer - Databricks (On-site only)

Ajmera Infotech builds planet-scale software for NYSE-listed clients, driving decisions that cant afford to fail. Our 120-engineer team specializes in highly regulated domainsHIPAA, FDA, SOC 2and delivers production-grade systems that turn data into strategic advantage.

• End-to-end impact Build full-stack analytics from lake house pipelines to real-time dashboards.
  

• Fail-safe engineering TDD, CI/CD, DAX optimization, Unity Catalog, cluster tuning.
  

• Modern stack Databricks, PySpark, Delta Lake, Power BI, Airflow.
  

• Mentorship culture Lead code reviews, share best practices, grow as a domain expert.
  

• Mission-critical context Help enterprises migrate legacy analytics into cloud-native, governed platforms.
  

• Compliance-first mindset Work in HIPAA-aligned environments where precision matters.
  

• Build scalable pipelines using SQL, PySpark, Delta Live Tables on Databricks.
  

• Orchestrate workflows with Databricks Workflows or Airflow; implement SLA-backed retries and alerting.
  

• Design dimensional models (star/snowflake) with Unity Catalog and Great Expectations validation.
  

• Deliver robust Power BI solutions dashboards, semantic layers, paginated reports, DAX.
  

• Migrate legacy SSRS reports to Power BI with zero loss of logic or governance.
  

• Optimize compute and cost through cache tuning, partitioning, and capacity monitoring.
  

• Document everything from pipeline logic to RLS rulesin Git-controlled formats.
  

• Collaborate cross-functionally to convert product analytics needs into resilient BI assets.
  

• Champion mentorship by reviewing notebooks, dashboards, and sharing platform standards.
  

• 5+ years in analytics engineering, with 3+ in production Databricks/Spark contexts.
  

• Advanced SQL (incl. windowing), expert PySpark , Delta Lake , Unity Catalog .
  

• Power BI mastery DAX optimization, security rules, paginated reports.
  

• SSRS-to-Power BI migration experience (RDL logic replication).
  

• Strong Git, CI/CD familiarity, and cloud platform know-how (Azure/AWS).
  

• Communication skills to bridge technical and business audiences.
  

• Databricks Data Engineer Associate cert.
  

• Streaming pipeline experience (Kafka, Structured Streaming).