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Staff Data Engineer - Hybrid

Pay
$125,760–188,640/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: $125,760 - $188,640 Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

Before you apply

Work authorization
Must already have the right to work in the USCandidates must be authorized to work in the US without company sponsorship

What you’ll work on

Full posting
  • Build small and medium-scale data pipelines and data products

  • Own Quote and Underwriting data pipelines hands-on

  • Build CI/CD capabilities aligned with Enterprise DevOps practices

  • Recommend data cleansing and quality solutions for complex data

  • Document technical requirements and provide operating guidance for users

From the employer’s posting
Accountable for building small or medium-scale pipelines and data products.
hands-on ownership of Quote and Underwriting data pipelines
Build and implement capabilities for continuous integration and continuous delivery aligned with Enterprise DevOps practices.
correcting problems and recommend data cleansing/quality solutions
Provide expert documentation and operating guidance for users of all levels.

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
Apply at The Hartford

Posting record

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Status in our records
Live
First seen by us
Sep 24, 202640 days ago
Recorded sightings
113
Last seen by us
Nov 4, 2026
Reposted
once since Sep 22, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.

How this job compares

Pay

In line with similar jobs

$126K–$189K against $127K–$190K, the middle half of what similar US postings state.

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 40

Similar jobs usually come down between day 5 and day 54.

From 10,733 similar postings that came down. Coming down is not always a hire.

The Hartford is hiring

23 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down at a usual pace
  • 9% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • AWS
  • Azure
  • GCP
  • Hadoop
  • Kafka
  • NoSQL
  • Oracle
  • S3
  • Snowflake
  • Spark
  • PySpark
Where the posting names them
- 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
- 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

Your next step

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

Applying through Workday

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  • Your application status lives in that employer’s Candidate Home, under the same sign-in.

Already applied? Track this application

Has The Hartford posted this job before?

Yes. We’ve followed one other Staff Data Engineer - Hybrid job there since April 2026. It came down after 41 days.

  1. HartfordCame down after 41 days, first seen Apr 10
  2. This jobUp 41 days so far, first seen Sep 24

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

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:

$125,760 - $188,640

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

Source details

View original posting ↗

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Selected passages from the saved posting. Check the full description for conditions and exceptions.

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: $125,760 - $188,640 Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
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

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