Unlock Your Future with Nexaminds! At Nexaminds, we're on a mission to redefine industries with AI. We're passionate about the limitless potential of artificial intelligence to transform businesses, streamline processes, and drive growth.

Join us on our visionary journey. We're leading the way in AI solutions, and we're committed to innovation, collaboration, and ethical practices. Become a part of our team and shape the future powered by intelligent machines.

If you're driven by ambition, success, fun, and learning, Nexaminds is where you belong. *]:pointer-events-auto [content-visibility:auto] supports-[content-visibility:auto]:[contain-intrinsic-size:auto_100lvh] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" data-turn-id="request-WEB:2093ca9d-d6bb-4dac-9795-2b28cd5013d9-1" data-testid="conversation-turn-4" data-scroll-anchor="true" data-turn="assistant"> Nexaminds is looking for a Senior Data Engineer to lead the development, optimization, and scaling of our data solutions. The ideal candidate has hands-on expertise building end-to-end pipelines on Databricks and enjoys working in a fast-paced, highly collaborative environment.

Qualifications

we are looking for: 5+ years Data Engineering in production Azure environments — Python, SQL, Spark Python: production-grade OOP, config-driven design, no hardcoding, type annotations PySpark / Spark: DataFrames, schema enforcement, partitioning, performance tuning SQL: advanced window functions, CTEs, incremental load patterns, Delta Lake DML (MERGE, UPDATE, DELETE) Azure Data Factory: parameterised pipelines, linked services, triggers, IR configuration Azure Databricks: notebooks, Jobs API, DLT, cluster configuration, Unity Catalog access ADLS Gen2, Delta Lake / Parquet format , Medallion store patterns Testing discipline: pytest, unit and integration tests, data quality assertions Git: feature branching, PR workflow, commit discipline, code review

Nice To Have

: Scala: Spark Dataset API, typed transformations, sbt build tooling Healthcare data formats: EDI X12 (837/835/834), FHIR R4 resource parsing Delta Lake: schema evolution, time travel, OPTIMIZE, VACUUM, Z-ordering dbt (data build tool) for SQL transformation layering and lineage documentation Databricks Asset Bundles (DABs) for pipeline-as-code deployment DP-203 Azure Data Engineer Associate certification Job duties: Design and build the core reusable ingestion engine in Python and ADF — parameterised, config-driven, zero hardcoding Build Python ingestion modules: file readers, schema validators, format handlers (CSV, EDI X12, FHIR R4, Parquet, JSON) Implement PySpark / Scala transformation components for batch and streaming at scale on Azure Databricks Write config-driven SQL data models for Bronze, Silver, Gold medallion transformations Develop metadata-driven validation layer: null checks, type enforcement, range rules, referential integrity Build reusable utility libraries: logging, error handling, retry logic, dead-letter routing Implement Databricks notebooks and DLT (Delta Live Tables) pipelines for declarative transformations Build and maintain the onboarding template library v1 and v2 — parameterised, documented, production-ready Onboard Provider, Claims, Member, Eligibility, and Reference data domains using the framework Write unit tests, integration tests, and data contract tests (pytest, Great Expectations or equivalent) Optimise Spark jobs: partitioning, caching, broadcast joins, Z-ordering on Delta tables Participate in code review, follow GitHub branching standards, and contribute to documentation What you can expect from us Here at Nexaminds, we're not your typical workplace. We're all about creating a friendly and trusting environment where you can thrive. Why does this matter?

Well, trust and openness lead to better quality, innovation, commitment to getting the job done, efficiency, and cost-effectiveness.

RAP Engineer