Senior Staff Data Engineer

TL;DR

Senior Staff Data Engineer (Data Engineering): Building end-to-end data pipelines and governed data products for Employee Benefits Sales, from ingestion and transformation to delivery across the organization with an accent on cloud/hybrid architectures and data quality. Focus on designing and optimizing Quote and Underwriting data pipelines, integrating complex datasets, and enabling continuous integration/continuous delivery for data engineering practices.

Company

hirify.global is an insurance company shaping data-driven decision-making across sales and underwriting.

What you will do

• Build small-to-medium scale pipelines and data products using ELT to acquire, integrate, and operationalize data.
• Shape solution architecture by influencing end-to-end design and independently reviewing and integrating complex data (type, quality, volume).
• Implement CI/CD capabilities aligned with Enterprise DevOps practices and ensure data engineering practices (source control, branching, issue tracking, access) are followed.
• Rapidly architect, design, prototype/POC, implement, and optimize cloud/hybrid architectures.
• Research and apply big data methodologies and technologies (e.g., AWS, Hadoop/EMR, Spark, Kafka, Snowflake) for project-level hybrid hosting.
• Document technical requirements and provide expert documentation and operating guidance for users; support roadmaps and implementation strategy.

Requirements

• Work authorization: Must be authorized to work in the US without company sponsorship.
• 8+ years of data engineering experience with distributed systems, data warehousing, SQL/NoSQL, ETL tools, CI/CD, big data, and cloud technologies (AWS/Azure).
• Hands-on experience with Snowflake, Oracle, Informatica Cloud/PowerCenter, and GitHub.
• Hands-on knowledge of replication/mass ingestion tools (e.g., Qlik, Informatica mass ingestion, Shareplex, OpenFlow, DMS).
• Familiarity with ETL using PySpark/Python and Snowflake native features; familiarity with AWS services such as EMR, S3, and Lambda.
• Hands-on experience with AWS Bedrock and Google Vertex; familiarity with AI tools/tech stack.

Culture & Benefits

• Hybrid work schedule with expectation to work in an office location (Hartford, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday).
• Annualized base pay range is provided as part of total compensation, with potential bonuses and long-term incentives.
• Growth path toward technical leadership with hands-on ownership of Quote and Underwriting data pipelines.