Job description

Sr Staff Data Engineer - GE07DE 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 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 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 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 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 Compensation The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $135,040 - $202,560 The posted salary range reflects our ability to hire at different position titles and levels depending on background and experience. Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits

Requirements

Must-haves

Sr Staff Data Engineer - GE07DE Staff Data Engineer - GE07CE
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).
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
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.
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
Certifications on AI foundation

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

awssqlazurepythongcpai

Platform: workday
Effort: long