Staff Data Reliability Engineer - Hybrid

The Hartford; Northern (KY); Hybrid; USD 128,000 - 191,000; Full time

Job summary

The Hartford is seeking a dedicated Data Reliability Engineer to focus on the integrity, quality, and availability of data assets and pipelines. This role partners with the SRE team to ensure trustworthy data products for downstream consumers and will operate in a hybrid model across multiple U.S.

office locations. Key responsibilities include establishing data SLOs, implementing observability, and automating data validation and runbooks.

Qualifications

• Bachelor's degree and 5+ years of experience in an Infrastructure, Data, or related technology organization with increasing responsibilities as a hands-on technologist.
• 3+ years of Data Engineering, Data Quality, or specialized SRE experience 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).

Responsibilities

• Establish and enforce Data Service Level Objectives focused on data freshness, completeness, and accuracy across critical data products.
• Implement advanced data observability tools to monitor the data journey and detect data quality issues in real-time.
• Collaborate with Data Engineering to embed reliability into data pipelines built on Informatica, Python/PySpark, on EMR/Hadoop and cloud services.
• Automate data validation, reprocessing, backfilling, and other manual tasks to reduce toil.
• Lead data-focused incident response and post-mortems to ensure fast recovery.
• Create and automate runbooks for data pipeline failures, quality issues, and data recovery scenarios.

Skills

Data Reliability

Data Engineering

Data Quality

SRE

Snowflake

AWS/GCP

ETL pipelines

SQL Server SSIS/SSMS

Informatica

Python/PySpark

EMR/Hadoop

Data Observability

Big Data

Education

Bachelor's degree

Tools

Informatica

SQL Server SSIS/SSMS

Snowflake

AWS

GCP

EMR/Hadoop

Monte Carlo

Bigeye

Astro Observe

Datafold

Job description

Staff 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 Data 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 - $191,400

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

Perks & Benefits

Every day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. We’re devoted to finding innovative ways to serve our customers, communities and employees—continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable? That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it’s these values that drive all of us to do more and to do better every day.