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Staff Data Engineer - Hybrid

Hartford, CT

Pay
$135,040–202,560/year · Base — pay source
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.
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Work setup
Unconfirmed
Employment
Unconfirmed

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
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.
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Apply at Thehartford

What you’ll work on

Full posting
  • You’ll work on modern, cloud‑based data platforms to ensure high‑quality, governed data products that drive operational efficiency, analytics, and decision‑making.

  • Build and implement capabilities for continuous integration and continuous delivery aligned with Enterprise DevOps practices.

  • Document technical requirements and present complex technical concepts to audiences of varying sizes and levels.

From the employer’s posting
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.
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
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

What you’ll bring

All qualifications

Core experience

  • 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
  • Hands-on experience with AWS Bedrock and Google Vertex
Qualification wording
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
Hands-on experience with AWS Bedrock and Google Vertex

Tools in this posting

  • SQL
  • AWS
  • Kafka
  • NoSQL
  • Oracle
  • S3
  • Snowflake
  • Spark
  • Python
  • Hadoop
  • Google Cloud (GCP)
  • Azure
  • PySpark
Source — Tool mentions in context
- 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
- 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)
- 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.
- 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
- 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 - Hands-on experience with AWS Bedrock and Google Vertex Compensation
- 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 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

Job description

View original posting ↗

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

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on thehartford.wd5.myworkdayjobs.com. The employer’s form will show what is required.

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Source & posting history

View original posting ↗

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Pay
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.
Location & working pattern

Hartford, CT

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:
More source context
- 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)
Work authorization
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
Status in our records
Active
First seen by us
Sep 24, 2026
Recorded sightings
40
Last seen by us
Oct 9, 2026

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