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Databricks Engineer - Commercial Insurance - Fulltime

Databricks Engineer - Commercial Insurance - Fulltime

Acunor IncColumbus, OH, United States
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ob Title : Data Engineer (Databricks + Azure)

Client : One of our Consulting Clients (Global Analytics & Digital Transformation Firm)

Location : Columbus, OH (Remote / Hybrid)

Duration : Full-Time

About the Role

We are seeking a highly skilled Data Engineer with deep expertise in Databricks and Azure Cloud to join a decision analytics and data engineering team within one of our global consulting clients. The role involves building, optimizing, and maintaining large-scale data pipelines that fuel enterprise analytics, reporting, and AI-driven insights-primarily supporting clients in the insurance and financial services domains .

Key Responsibilities

Data Pipeline Development & Optimization

  • Design, build, and enhance ETL / ELT data pipelines using Azure Data Factory , Databricks (PySpark, SQL, Python) , and related services.
  • Develop and manage Delta Live Tables , Autoloader , and Unity Catalog within the Databricks ecosystem for structured, incremental data processing.
  • Implement data ingestion, transformation, and validation frameworks that ensure high performance, scalability, and reliability.
  • Monitor data pipelines, troubleshoot issues, and ensure optimal system performance and SLA adherence.

Data Modeling & Architecture

  • Collaborate with business analysts and reporting teams to define logical and physical data models supporting analytical and operational needs.
  • Implement data warehousing and lakehouse solutions using Azure Data Lake and Delta Lake .
  • Optimize data structures for query performance, cost efficiency, and reusability.
  • Data Quality, Governance & Automation

  • Design and implement robust data quality checks and validation mechanisms to maintain integrity across sources and transformations.
  • Automate repetitive processes using scripts, parameterized pipelines, and reusable frameworks.
  • Conduct periodic audits and compliance checks aligned with governance policies.
  • Contribute to metadata management, documentation, and lineage tracking.
  • Required Skills & Experience

  • 7 12 years of experience in Data Engineering with proven expertise in Databricks and Azure Cloud ecosystems.
  • Strong hands-on experience in PySpark , Python , and SQL for data transformation, validation, and performance tuning.
  • Solid understanding of Delta Lake architecture , ETL / ELT frameworks , and data warehousing principles.
  • Proficiency with Azure services including Data Factory (ADF) , Data Lake (ADLS) , and Databricks Notebooks .
  • Experience with Delta Live Tables , Unity Catalog , and Autoloader for batch and streaming data processing.
  • Strong background in data modeling , performance optimization , and automation scripting .
  • Familiarity with Agile methodologies and DevOps-based deployment practices (Git, CI / CD preferred).
  • Strong analytical, communication, and problem-solving skills to collaborate effectively across diverse teams.
  • Preferred : Exposure to insurance, healthcare, or financial services data ecosystems.
  • Nice to Have

  • Experience in data migration projects (on-prem to cloud or multi-cloud).
  • Familiarity with Delta Sharing , Databricks SQL Warehouses , or MLflow for advanced use cases.
  • Experience with data cataloging, lineage, or quality frameworks such as Purview, Collibra, or Great Expectations.
  • Exposure to BI / reporting tools like Power BI or Tableau for end-to-end integration understanding.
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    Commercial Insurance • Columbus, OH, United States

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