Data Engineer - Hybrid

Position: Staff Data Engineer - Hybrid
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 Senior Staff Data Engineer supporting Employee Benefits Sales, you will play a key role in shaping how Sales and Underwriting 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 Underwriting, Product and Enterprise Data teams.

The position offers a strong growth path toward Technical Leadership, with hands-on ownership of Quote and Underwriting 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).
** Responsibilities:
*** 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 Dev Ops practices.
* Accountable for team development and influencing pipeline tool decisions
* Accountable for data engineering practices (e.g. Source code management, branching, issue tracking, access, etc.) to be followed for the data pipeline
* Independently review, prepare, design and integrate complex (type, quality, volume) data, correcting problems and recommend data cleansing/quality solutions
* 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) 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 and recommend all technology-based decisions for tools and frameworks for effective delivery
* Support the development and implementation of project and portfolio strategy, roadmaps and implementation
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* Qualifications:

*** 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.
* 8+ years of data engineering experience and best practices in Distributed systems, Data warehousing solutions SQL and No

SQL, ETL tools, CICD, Bigdata, Cloud Technologies (AWS/AZURE), Python/Spark, Data mesh and Data Lake, Data Fabric
* Must have hands on experience in Snowflake, Oracle, Informatica Cloud/Power center, Github
* Must have hands-on experience and knowledge on replication tools like Qlik, Informatica mass ingestion, Shareplex, open flow, DMS
* Must be familiar with ETL using Pyspark/Python/snowflake native features
* Must be familiar with AWS services…