Pay
In line with similar jobs
$128K–$191K 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.
Staff Data Site Reliability Engineer - Hybrid
Charlotte, NC
Live, first seen by us 76 days ago- Pay
$127,600–191,400/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: $127,600 - $191,400 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 US
Candidates must be authorized to work in the US without company sponsorship
What you’ll work on
Full postingSet and enforce data SLOs for freshness, completeness, and accuracy
Implement data observability to catch quality anomalies, schema drift, and delays
Embed reliability patterns into Informatica and PySpark pipelines with Data Engineering
Automate data validation, reprocessing, and backfilling to reduce toil
Lead response and post-incident reviews for data incidents
From the employer’s posting
Establish and enforce Data Service Level Objectives (SLOs) focused on data freshness, completeness, and accuracy across critical data products.
Implement advanced data observability tools to monitor the entire data journey
Collaborate with Data Engineering to embed reliability patterns into data pipelines built using
Automate data validation, data reprocessing, data backfilling, and other manual operational tasks
Lead the response and resolution for data-related incidents (e.g., corrupt data, delayed reporting)
Education & alternatives
- 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. - Bachelors degree and 5+ year’s overall experience in an Infrastructure, Data or related technology organization with increasing responsibilities as a hands-on technologist. - 3+ year experience in Data Engineering, Data Quality, or a specialized SRE role within an enterprise data environment.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 19, 202676 days ago
- Recorded sightings
- 199
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 76
Up longer than most. 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
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.
- C#
- Python
- SQL
- AWS
- GCP
- Hadoop
- Snowflake
- SQL Server
- PySpark
Where the posting names them
- Hands-on experience with ETL pipelines using SQL Server Integration Services (SSIS) and SQL Server Management Studio (SSMS). - Nice to have: Collaborate with application teams to support and enhance software solutions utilizing the .NET framework (C# or VB.NET) interacting with SQL backend architectures. Develop and maintain robust enterprise web applications using ASP.NET (4.5 and 4.6) - Hands-on experience in pipeline development and support using technologies like Informatica, Python/Pyspark, and distributed compute (EMR/Hadoop).
- Data Observability: Implement advanced data observability tools to monitor the entire data journey—from ingestion to consumption—detecting data quality anomalies, schema drifts, and pipeline delays in real-time. - Pipeline Resiliency & Automation: Collaborate with Data Engineering to embed reliability patterns into data pipelines built using Informatica, Python/Pyspark, and running on platforms like Amazon EMR/Hadoop, Informatica and cloud native services. - Toil Elimination in Data Operations: Automate data validation, data reprocessing, data backfilling, and other manual operational tasks within the data lifecycle to reduce toil and improve operational efficiency.
- Nice to have: Collaborate with application teams to support and enhance software solutions utilizing the .NET framework (C# or VB.NET) interacting with SQL backend architectures. Develop and maintain robust enterprise web applications using ASP.NET (4.5 and 4.6) - Hands-on experience in pipeline development and support using technologies like Informatica, Python/Pyspark, and distributed compute (EMR/Hadoop). - Experience in designing and implementing data quality checks, data validation frameworks, and data governance standards.
- Hands-on experience with data warehousing and data lake technologies, including Snowflake, and cloud environments (AWS/GCP). - Hands-on experience with ETL pipelines using SQL Server Integration Services (SSIS) and SQL Server Management Studio (SSMS). - Nice to have: Collaborate with application teams to support and enhance software solutions utilizing the .NET framework (C# or VB.NET) interacting with SQL backend architectures. Develop and maintain robust enterprise web applications using ASP.NET (4.5 and 4.6)
- 3+ year experience in Data Engineering, Data Quality, or a specialized SRE role within an enterprise data environment. - Hands-on experience with data warehousing and data lake technologies, including Snowflake, and cloud environments (AWS/GCP). - Hands-on experience with ETL pipelines using SQL Server Integration Services (SSIS) and SQL Server Management Studio (SSMS).
- Expertise implementing AIOps to monitor, manage and self-heal data pipelines, using machine learning principles for anomaly detection. - Experience with prompt engineering, implementing AWS or Google AI services, AI enabled automation for data quality, reliability and pipeline performance management. - Expertise defining and implementing of DataOps practices
Your next step
Complete your application on thehartford.wd5.myworkdayjobs.com. The employer’s form will show what is required.
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Already applied? Track this application
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
Staff Site Reliability Engineer - IE07KE
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.
The Hartford is seeking a dedicated Staff Data Site Reliability Engineer (DRE) to focus specifically on the integrity, quality, and availability of our data assets and pipelines. This role is a key partner to the SRE team, concentrating on the "data journey" layer. You will apply SRE principles to data pipelines, ensuring our data products are consistently trustworthy and reliable for all downstream consumers.
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).
Key Responsibilities
- Data Reliability & Quality: Establish and enforce Data Service Level Objectives (SLOs) focused on data freshness, completeness, and accuracy across critical data products.
- Data Observability: Implement advanced data observability tools to monitor the entire data journey—from ingestion to consumption—detecting data quality anomalies, schema drifts, and pipeline delays in real-time.
- Pipeline Resiliency & Automation: Collaborate with Data Engineering to embed reliability patterns into data pipelines built using Informatica, Python/Pyspark, and running on platforms like Amazon EMR/Hadoop, Informatica and cloud native services.
- Toil Elimination in Data Operations: Automate data validation, data reprocessing, data backfilling, and other manual operational tasks within the data lifecycle to reduce toil and improve operational efficiency.
- Incident and Problem Management (Data Focus): Lead the response and resolution for data-related incidents (e.g., corrupt data, delayed reporting), ensuring fast recovery and effective post-incident reviews (blameless post-mortems).
- Runbook Creation & Automation (Data Focus): Develop and automate sophisticated, data-aware runbooks for common data pipeline failures, data quality issues, and data recovery scenarios.
Required Skills & Experience
- 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.
- Bachelors degree and 5+ year’s overall experience in an Infrastructure, Data or related technology organization with increasing responsibilities as a hands-on technologist.
- 3+ year experience in Data Engineering, Data Quality, or a specialized SRE role within an enterprise data environment.
- Hands-on experience with data warehousing and data lake technologies, including Snowflake, and cloud environments (AWS/GCP).
- Hands-on experience with ETL pipelines using SQL Server Integration Services (SSIS) and SQL Server Management Studio (SSMS).
- Nice to have: Collaborate with application teams to support and enhance software solutions utilizing the .NET framework (C# or VB.NET) interacting with SQL backend architectures. Develop and maintain robust enterprise web applications using ASP.NET (4.5 and 4.6)
- Hands-on experience in pipeline development and support using technologies like Informatica, Python/Pyspark, and distributed compute (EMR/Hadoop).
- Experience in designing and implementing data quality checks, data validation frameworks, and data governance standards.
- Hands on experience in software or cloud engineering. Familiarity with cloud service providers and their core capabilities (compute, containers, databases, APIs etc.).
- In depth and hands on experience with data observability concepts and tools for monitoring data in motion and at rest (e.g., Monte Carlo, Bigeye, Astro Observe, Datafold, custom solutions).
- A strong understanding of the "data journey" and the impact of data issues on business outcomes.
- Expertise implementing AIOps to monitor, manage and self-heal data pipelines, using machine learning principles for anomaly detection.
- Experience with prompt engineering, implementing AWS or Google AI services, AI enabled automation for data quality, reliability and pipeline performance management.
- Expertise defining and implementing of DataOps practices
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:
$127,600 - $191,400Equal 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
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Source excerptsSelected 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: $127,600 - $191,400 Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
- Location & working pattern
Charlotte, NC
The Hartford is seeking a dedicated Staff Data Site Reliability Engineer (DRE) to focus specifically on the integrity, quality, and availability of our data assets and pipelines. This role is a key partner to the SRE team, concentrating on the "data journey" layer. You will apply SRE principles to data pipelines, ensuring our data products are consistently trustworthy and reliable for all downstream consumers. 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). Key Responsibilities
- Work authorization
Required Skills & Experience - 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. - Bachelors degree and 5+ year’s overall experience in an Infrastructure, Data or related technology organization with increasing responsibilities as a hands-on technologist.