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Manager of Data Engineering

Manager Data Engineering - GE07AE

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 Manager of  Data Engineering within Workers’ Compensation and Group Benefits Claims Data Science to lead a team of Data Engineers to design, develop, and implement modern and sustainable data assets to fuel machine learning and artificial intelligence solutions across a wide range of strategic initiatives designed to drive efficiency within Workers’ Compensation and Group Benefits claims process.

As a Manager of Data Engineering, you will lead and mentor a small team through the entire software development lifecycle process in support of continuous data delivery, while growing your knowledge of emerging technologies. We use the latest data technologies, software engineering practices, MLOPs, Agile delivery frameworks, and are passionate about building well-architected and innovative solutions that drive business value. This cutting edge and forward focused organization presents the opportunity for collaboration, self-organization within the team, and visibility as we focus on continuous business data delivery.

This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).

Responsibilities:

  • Lead and mentor data engineers to deliver and maintain reusable and sustainable data assets and production pipelines that assist the functional business units in meeting their strategic objectives
  • Prototype and lead deployment of high impact innovations, catering to changing business needs, by leveraging new technologies
  • Consult with cross-functional stakeholders in the analysis of short and long-range business requirements and recommend innovations which anticipate the future impact of changing business needs. Distill these requirements into user stories and action items for team members.
  • Formulate logical statements of business problems and devise, test and implement efficient, cost-effective application program solutions
  • Identify and validate internal and external data sources for availability and quality. Work with SMEs to describe and understand data lineage and suitability for a use case
  • Create data assets and build data pipelines that align to modern software development principles for further analytical consumption. Perform data analysis to ensure quality of data assets
  • Develop code that enables real-time modeling solutions to be ingested into front-end systems
  • Produce code artifacts and documentation using GitHub for reproducible results and hand-off to other data science teams and ensure high quality standards for direct reports

Qualifications:

  • 6+ years of relevant experience recommended
  • Bachelor’s degree in Computer Science, Engineering, IT, MIS, or a related discipline
  • Experience in managing Data Engineering initiatives in an Agile environment
  • Expertise in Python and SQL
  • Proficiency in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON
  • Proficiency in ETL concerning metadata management and data validation
  • Expertise in Unix and Git
  • Proficiency in Automation tools (Autosys, Cron, Airflow, etc.)
  • Proficiency with AWS Services (i.e. S3, EMR, etc) a plus
  • Proficiency with Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus
  • Able to communicate effectively with both technical and non-technical teams
  • Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution
  • Experience with leading project execution and driving change to core business processes through the innovative use of quantitative techniques
  • Experience building CICD pipeline using Jenkins or equivalent.
  • Experience with Solution Design and Architecture of data and ML pipelines as well as integrating with Enterprise systems.
  • Good understanding and experience building orchestration framework for real-time and batch services.
  • Experience building asynchronous or event-driven services in cloud environment.
  • Familiar with BI tools (Tableau, PowerBI, ThoughtSpot, etc)
  • Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution
  • Experience with leading project execution and driving change to core business processes through the innovative use of quantitative techniques
  • Candidate 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.

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:

$127,200 - $190,800

Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us | Culture & Employee Insights | Diversity, Equity and Inclusion | Benefits

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Average salary estimate

$159000 / YEARLY (est.)
min
max
$127200K
$190800K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Manager of Data Engineering, The Hartford

As a Manager of Data Engineering at The Hartford, based in Hartford, CT, you’ll have the exciting opportunity to foster innovation within the Workers’ Compensation and Group Benefits Claims Data Science team. We’re passionate about using technology to disrupt traditional insurance practices, and in this role, you will lead a talented team of Data Engineers dedicated to designing, developing, and implementing sustainable data solutions. You'll help to fuel machine learning and AI initiatives that drive significant improvements in our claims processes. Your responsibilities will include mentoring your team through every stage of the software development lifecycle and ensuring seamless data delivery. You’ll be hands-on, crafting reusable data assets and production pipelines that align with business objectives, while also being a guiding force in adopting emerging technologies. At The Hartford, we value collaboration and creativity, providing you with a hybrid work schedule and the flexibility to thrive. If you have a solid background in Python, SQL, and a knack for translating complex technical concepts into actionable business strategies, we want to hear from you. Join us, and be part of a company that is making meaningful contributions beyond just policies and coverages!

Frequently Asked Questions (FAQs) for Manager of Data Engineering Role at The Hartford
What are the primary responsibilities of a Manager of Data Engineering at The Hartford?

The primary responsibilities of a Manager of Data Engineering at The Hartford include leading a team of Data Engineers in delivering sustainable data assets, mentoring team members throughout the software development lifecycle, and implementing innovative data solutions that enhance Workers’ Compensation and Group Benefits claims processes. You will also collaborate with stakeholders to analyze business requirements and ensure data quality.

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What qualifications are needed for the Manager of Data Engineering position at The Hartford?

To qualify for the Manager of Data Engineering position at The Hartford, candidates should have at least 6 years of relevant experience, a Bachelor's degree in Computer Science, IT, or a related field, and expertise in Python and SQL. Familiarity with ETL processes, cloud data services, and Agile methodologies is also essential for this role, along with strong communication skills to bridge technical and non-technical discussions.

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What technologies will a Manager of Data Engineering at The Hartford work with?

A Manager of Data Engineering at The Hartford will work with a variety of cutting-edge technologies. This includes programming languages like Python and SQL, data ingestion tools like Hadoop and Spark, cloud platforms such as AWS, and automation frameworks like Airflow. You will also engage with real-time modeling solutions and BI tools to drive decision-making across the organization.

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How does The Hartford promote professional growth for its Manager of Data Engineering?

The Hartford promotes professional growth for its Manager of Data Engineering by encouraging continuous learning and mentoring. You will have the opportunity to work with leading technologies, collaborate with cross-functional teams, and participate in the development of strategic initiatives that drive efficiency and innovation. The organization also provides resources for career advancement and skills development.

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What is the work environment like for a Manager of Data Engineering at The Hartford?

The work environment for a Manager of Data Engineering at The Hartford is a dynamic blend of collaboration and innovation. With a hybrid work model, you’ll be expected to work in the office three days a week, which fosters teamwork and allows for real-time problem-solving. The culture emphasizes creativity, support, and the importance of achieving collective goals while maintaining a focus on personal and professional development.

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Common Interview Questions for Manager of Data Engineering
What experience do you have leading a data engineering team?

When answering this question, focus on your leadership style, specific projects you've managed, and the technologies used. Emphasize your ability to mentor team members, streamline workflows, and implement best practices that elevate team performance.

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Can you explain your experience with data pipeline construction and management?

Discuss specific tools and methodologies you've used in building data pipelines. Highlight your familiarity with ETL processes, data ingestion techniques, and the importance of data quality and validation, showcasing how you've ensured the reliability of end-to-end workflows.

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How do you stay updated on the latest data engineering technologies?

Share your strategies for continuous learning, such as following industry blogs, attending webinars, and participating in professional networks. Mention any specific technologies you’ve had recent exposure to and how you’ve applied new knowledge to past projects.

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Describe a challenging data engineering problem you've encountered.

Provide a specific example of a data-related challenge you faced, the steps you took to diagnose the issue, and how you ultimately resolved it. This will demonstrate your problem-solving skills and ability to adapt under pressure.

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How do you ensure that your team meets project deadlines?

Discuss project management techniques you use, such as Agile methodologies, regular check-ins, and clear communication channels. Highlight your focus on setting achievable milestones and allowing room for feedback to ensure timely project delivery.

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What role does collaboration play in data engineering projects?

Explain the significance of cross-functional collaboration in data engineering, emphasizing how it enhances project outcomes. Share examples of successful collaborations with data scientists, business analysts, and IT teams to illustrate your point.

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How would you handle a disagreement within your team?

Outline your approach to conflict resolution, which might include facilitating open discussions, seeking input from all team members, and finding a common ground. Emphasize the importance of maintaining a positive team dynamic.

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What are the key metrics you track for data engineering projects?

Discuss the importance of metrics related to data quality, pipeline performance, and team productivity. Mention specific KPIs you measure and how they inform decision-making and continuous improvement in project delivery.

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How do you approach the documentation of data engineering processes?

Highlight the necessity of comprehensive documentation for knowledge sharing and ensuring replicability. Discuss the tools you use for documentation and how you foster a culture of thorough record-keeping among your team.

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What is your experience with cloud services, specifically AWS?

Detail your experience with AWS services that you've used in data engineering, such as S3 or Redshift. Talk about specific projects where you effectively leveraged cloud technology to enhance data processing and analytics capabilities.

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The Hartford is a leader in property and casualty insurance, group benefits and mutual funds. We have a passion for helping people and businesses prepare for the unexpected, protect what is uniquely important to them, and prevail when the unforese...

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Full-time, hybrid
DATE POSTED
March 30, 2025

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