Senior Data Engineer

Hylant • Elkhart, NV

3d • Remote

About The Position

The Senior Data Engineer will build, integrate, and operationalize Hylant’s enterprise data architecture on its Databricks and Azure platform. The role translates architectural designs and analytical requirements into reliable, scalable data pipelines and business-ready datasets, working closely with the Lead Data Architect to align solutions with defined standards, patterns, and governance requirements.

This is a fully remote position open to candidates located within the United States. Periodic in-person attendance may be required for team meetings, onsite collaboration, or other business-related functions, with reasonable advance notice. Work is generally performed in a home office or standard office environment with limited exposure to physical risk or physical effort. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

Requirements

• 5–7+ years of experience as a Data Engineer, including designing, implementing, and validating production-grade data pipelines.
• Hands-on experience with Azure Databricks, Azure Data Factory, Delta Lake, Unity Catalog, and core Azure cloud services.
• Strong proficiency in SQL and PySpark for data transformation and pipeline development.
• Experience implementing data quality checks, reconciliations, and validation processes in complex data environments.
• Experience owning or contributing to CI/CD pipelines for data platforms; Azure DevOps Pipelines preferred.
• Ability to troubleshoot and resolve complex data, pipeline, and performance issues.
• Strong collaboration and communication skills, with the ability to bridge technical and non-technical stakeholders.
• Must be legally authorized to work in the United States.

Nice To Haves

• Bachelor’s degree in computer science, engineering, data science, or a related field, or equivalent practical experience (desired).
• Insurance industry experience in brokerage, policy administration, claims, billing, underwriting, or risk data; preferred but not required.
• Exposure to applying AI or automation within data engineering workflows.
• Exposure to Power BI.

Responsibilities

• Design, build, and maintain data transformation logic, business rules, and analytics-ready datasets using Databricks notebooks, PySpark, and SQL.
• Develop, orchestrate, and monitor ETL/ELT pipelines using Azure Databricks and Azure Data Factory, including scheduling, dependency management, and job performance tuning.
• Create target schemas, curated tables, and analytics-ready data layers aligned with architectural designs and business requirements, including source-to-target mapping, historical data loads, and backfills for new data domains.
• Implement and enforce data governance, security, and access controls within Unity Catalog, including group-based grants, attribute-based access policies, and row- and column-level security, in accordance with Data Architecture team standards.
• Conduct data profiling, validation, reconciliation, and system integration testing to ensure end-to-end data quality, accuracy, and reliability; partner with source system owners and downstream consumers to investigate and resolve discrepancies.
• Serve curated, trusted datasets through Databricks SQL and Power BI datasets to support operational, financial, and analytical reporting.
• Own the CI/CD process for Databricks and Azure Data Factory using Azure DevOps Pipelines.
• Monitor, tune, and optimize the data platform for performance and cost, including cluster sizing, autoscaling, and job execution efficiency.
• Participate in agile delivery as part of the Data & Digital Solutions team, including sprint planning, backlog refinement, and delivery commitments.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior