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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operationalizing data architectures using Azure Databricks and Azure Data Factory, with a strong focus on data governance, pipeline development, and performance optimization. Proficient in SQL and PySpark for data transformation, with experience in CI/CD processes and collaboration across technical and non-technical teams.
Highest-signal resume keywords
Azure DatabricksAzure Data FactorySQLPySparkCI/CD Pipelines
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DevelopmentData TransformationData Quality ChecksData ValidationData GovernanceETL/ELT ProcessesData ProfilingSystem Integration TestingPerformance TuningData Architecture
Soft Skills
CollaborationCommunicationProblem-Solving
Tools & Technologies
Azure DevOpsPower BIDelta LakeUnity Catalog
Industry Keywords
Insurance Industry ExperienceData EngineeringAgile Delivery
Tech Stack
Tools & technologiesAzureCloudETLPySparkSQLUnity
About the role
Key responsibilities & impact- Build, integrate, and operationalize Hylant’s enterprise data architecture on Databricks and Azure
- Translate architectural designs and analytical requirements into reliable, scalable data pipelines and business-ready datasets
- Work closely with the Lead Data Architect to align data solutions with standards, patterns, and governance requirements
- Design, build, and maintain 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
- Create target schemas, curated tables, and analytics-ready data layers, including source-to-target mapping, historical data loads, and backfills
- Implement data governance, security, and access controls within Unity Catalog
- Conduct data profiling, validation, reconciliation, and system integration testing
- Investigate and resolve data discrepancies with source system owners and downstream consumers
- Serve curated datasets through Databricks SQL and Power BI datasets for 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
- Participate in agile delivery, including sprint planning, backlog refinement, and delivery commitments
Requirements
What you’ll need- Bachelor’s degree in computer science, engineering, data science, or a related field, or equivalent practical experience (desired)
- 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
- Insurance industry experience preferred but not required
- Exposure to applying AI or automation within data engineering workflows is a plus
- Exposure to PowerBI is a plus
- Must be legally authorized to work in the United States
Benefits
Comp & perks- Fully remote work arrangement
- Periodic in-person attendance with reasonable advance notice
- People-first culture
- Supported careers with purpose
- Family-oriented team environment