Senior Data Analytics Engineer
Job Summary
Job Description
- 5+ years in analytics engineering, with 3+ in production Databricks/Spark contexts.
- Advanced SQL, 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 certification.
- Streaming pipeline experience (Kafka, Structured Streaming).
- dbt, Great Expectations, or similar data quality frameworks.
- BI diversity—experience with Tableau, Looker, or similar platforms.
- Cost governance familiarity (Power BI Premium capacity, Databricks chargeback).
- Competitive compensation
- Flexible hybrid schedules
- Deeply technical culture where engineers lead the narrative
13 skills required
Job Details
Sr. Data Analytics Engineer – Power mission-critical decisions with governed insights
Ajmera Infotech builds planet-scale software for NYSE-listed clients, driving decisions that can’t afford to fail. Our 120-engineer team specializes in highly regulated domains—HIPAA, FDA, SOC 2—and delivers production-grade systems that turn data into strategic advantage.
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Why You’ll Love It
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.
Requirements
Key Responsibilities
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 rules—in 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.
Must-Have Skills
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.
Nice-to-Have Skills
Databricks Data Engineer Associate cert.
Streaming pipeline experience (Kafka, Structured Streaming).
dbt, Great Expectations, or similar data quality frameworks.
BI diversity—experience with Tableau, Looker, or similar platforms.
Cost governance familiarity (Power BI Premium capacity, Databricks chargeback).
Benefits
Benefits & Call-to-Action
Ajmera offers competitive compensation, flexible hybrid schedules, and a deeply technical culture where engineers lead the narrative. If you’re driven by reliable, audit-ready data products and want to own systems from raw ingestion to KPI dashboards—apply now and engineer insights that matter.
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