Staff Data Engineer - Hybrid

Staff Data Engineer - GE07CE
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

As a Staff Data Engineer supporting Employee Benefits Claims, you will play a key role in shaping how claims data is ingested, transformed, and delivered across the organization. You'll work on modern, cloud-based data platforms to ensure high-quality, governed data products that drive operational efficiency, analytics, and decision-making. This role combines deep technical expertise with strong partnership across Claims and Enterprise Data teams.

The position offers a strong growth path toward Technical Leadership, with hands-on ownership of claims data pipelines and opportunities to mentor and influence across teams.

This role will have a Hybrid work schedule, with the expectation of working in an office location (Hartford, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday).

• Accountable for building small or medium-scale pipelines and data products. End-to-End solution delivery involving multiple platforms and technologies with small to medium complexity or certain sub-systems of large, complex implementations, leveraging ELT solutions to acquire, integrate, and operationalize data
• Provides significant input to influence solution architecture
• Build and implement capabilities for continuous integration and continuous delivery aligned with Enterprise DevOps practices.
• Accountable for team development and influencing pipeline tool decisions
• Accountable for data engineer practices (e.g. Source code management, branching, issue tracking, access, etc.) followed for the product
• Independently review, prepare, design and integrate complex (type, quality, volume) data, correcting problems and recommend data cleansing/quality solutions to issues
• Provide expert documentation and operating guidance for users of all levels.
• Document technical requirements and present complex technical concepts to audiences of varying sizes and levels.
• Rapidly architect, design, prototype/POC, implement, and optimize Cloud/Hybrid architectures
• Research, experiment, and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake and Talend) with cloud/on premise hybrid hosting solutions, on a project level
• Implement, and test data processing pipelines, and data mining/data science algorithms on a variety of hosted settings (AWS,
• Client technology stacks)
• Stay up to date on emerging data and analytics technologies, tools, techniques, and frameworks. Evaluate, recommend, and
• influence all technology-based decisions for tools and frameworks for effective delivery
• Support the development and implementation of project and portfolio strategy, roadmaps and implementation

• Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
• 5+ years of data engineering experience and best practices in Distributed systems, Data warehousing solutions SQL and NoSQL, ETL tools, CICD, Bigdata, Cloud Technologies (AWS/AZURE),Python/Spark, Data mesh and Data Lake, Data Fabric
• Must have Snowflake and IDMC/ Informatica experience
• 2+ years of developing and operating production workloads in cloud infrastructure
• knowledge of agile/iterative methodologies and toolsets
• Ability to execute independently