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 LakeOptimize 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 NotebooksExperience with Delta Live Tables Unity Catalog , and Autoloader for batch and streaming data processing.Strong background in data modeling performance optimization , and automation scriptingFamiliarity 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 ExpectationsExposure to BI / reporting tools like Power BI or Tableau for end-to-end integration understanding.J-18808-Ljbffr
