Senior Staff Data Engineer

Responsibilities

• 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 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

Requirements

• 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 NoSQL, 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 such as EMR, S3, Lambda
• Certifications on Cloud services such as AWS/GCP and Snowflake
• Familiar with AI tools/tech stack
• Nice to have qualifications:
• Certifications on AI foundation
• Hands-on experience with AWS Bedrock and Google Vertex

Benefits

Additional Information

Sr Staff Data Engineer - GE07DE 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).

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