Senior Data Engineer

Plantation, United States | Posted on 01/08/2026

• Administer, optimize, and scale our Databricks Lakehouseenvironment, ensuring high performance, cost efficiency, and operational excellence.
• Develop, maintain, and enhance our data platforminfrastructure and security configurations using Terraform . This includes provisioning Databricks work spaces, SQL Endpoints, Unity Catalogobjects, and network components.
• Manage and enforce Unity Catalog for data governance, access control, andmetadata management.
• Implement and manage CI/CD pipelines for data pipelines, dbt projects, and infrastructure deployments using Git Hub Actions .
• Automate operational tasks, monitoring, and alerting for thedata platform.
• Implement and enforce Dev Sec Ops  principles, working closely with security teams to ensure compliance and manage/rotate credentialssecurely.
• Design and implement data ingestion patterns into Databricks using Delta Lake, optimizing
  for large-scale data processing and storage.
• Develop, optimize, and troubleshoot complex Spark jobs (PySpark/Scala) for data processing and transformation within Databricks.
• Manage and extend dataingestion pipelines using Airbyte (or similar modern tools like Fivetran, Stitch), including configuringconnectors, monitoring syncs, and ensuring data quality and reliabilityfrom diverse source systems (e.g., ERP, CRM, marketing, supply chain).
• Orchestrate and automate data pipelines and dbt models using
  
  Databricks Workflows and potentially integrating with other orchestrationtools.
• Collaborate with Analytics Engineers to translate business requirements into efficient and scalable data models using dbt (Data Build Tool).
• Implement dbt best practices for modularity, testing,documentation, and version control, ensuring seamless integration with Databricks.
• Partner effectively with Analytics Engineers, Data Scientists, and business stakeholders to deliver high-quality data solutions.
• Provide technical guidance and mentorship to junior team members, and champion data engineering best practices, code quality, and documentation standards.

• Education: Bachelor's degree in Computer Science, Data Engineering, or a related technical field required.
• Experience: 5+ years of progressive experience as a Data Engineer, with a strong focus on cloud-based data platforms.
• Deep Databricks Expertise: Extensive experience with Spark(PySpark/Scala), Delta Lake, Unity Catalog, Databricks SQL, and platformadministration.
• Data Modeling: Proven experience with dbt for data modeling, transformation, and testing.
• Infrastructure as Code (IaC): Strong proficiency with Terraform for defining,provisioning, and managing cloud infrastructure and Databricks resourcesas code.
• Dev Ops & CI/CD: Expertise in Git and Git Hub Actions for version control and implementing robust CI/CD pipelines.
• Programming: Proficiency in SQL and atleast one programming language (Pythonstrongly preferred, Scalais a plus).
• Data Architecture: Solid understanding of data warehousing, data lake, and lakehouse architectures.