Associate Data Engineer - Tech Catalyst Program; Columbus

Assoc Data Engineer - GE08BE

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.

Launch your career building scalable, intelligent data solutions powered by cloud and AI! The Hartford’s Tech, Data, Analytics & Cyber organization is hiring early career data engineers who are passionate about turning data into actionable insights and business value. The Tech Catalyst Program is a structured, immersive experience designed to accelerate your development as a modern data engineer. You will gain hands‑on experience building data products and pipelines while developing capabilities across data engineering, cloud platforms, and AI‑enabled data systems.

This program reflects our commitment to building a future‑ready workforce—equipping early career talent with in‑demand skills in data, cloud, and AI.

• Contribute to modern data engineering teams
• Design, build, and maintain scalable data pipelines and data products
• Develop ETL/ELT processes to ingest, transform, and curate structured and unstructured data
• Ensure data quality, reliability, and performance across data solutions
• Partner with data analysts, data scientists, and product teams to deliver business value
• Build cloud and platform capabilities
• Develop solutions using cloud‑native data platforms (AWS, with GCP exposure for AI capabilities)
• Work with modern tools such as Snowflake, Big Query, and cloud storage solutions
• Support data platform engineering, automation, and pipeline orchestration
• Contribute to data modernization initiatives, including migration to cloud environments
• Apply AI and data‑driven engineering
• Support AI/ML use cases by preparing and optimizing data for models
• Apply foundational understanding of machine learning workflows and supporting data pipelines
• Leverage AI‑assisted tools (including Google Vertex) to enhance productivity and data solutions
• Build awareness of responsible AI, data ethics, and governance practices
• Collaborate with data scientists to operationalize machine learning solutions
• Deliver business impact while growing your capabilities
• Translate business and analytical needs into scalable data solutions
• Communicate insights and technical concepts to diverse audiences
• Demonstrate adaptability and continuous learning across evolving tools and platforms
• Contribute to inclusive, collaborative, product‑focused team environments

• Structured learning and real‑world application: 10‑week immersive onboarding and technical training experience
• Continued capability‑building focused on modern data engineering, cloud, and AI
• Hands‑on delivery and exposure
• Placement on Agile, product‑aligned teams supporting enterprise data solutions
• Exposure to business‑critical use cases across insurance and analytics domains
• Support and career growth
• Mentorship, coaching, and peer learning designed to accelerate development
• Opportunities to build a strong internal network and long‑term career path

Passionate about using data to drive business and customer outcomes, curious about emerging technologies including data platforms, AI, and cloud; adaptable and comfortable working in evolving, ambiguous environments; strong problem solver with data‑driven thinking skills; effective communicator who collaborates well across teams.

• Bachelor’s degree (expected graduation: May
  2027) in Computer Science, Data Engineering, Data Analytics, Information Technology, Engineering, or related field
• Minimum GPA of 3.0 at time of graduation
• Authorization to work in the U.S. without sponsorship now or in the future

• Foundational experience with SQL and relational databases
• At least one programming language (Python, Java, or R)
• Understanding of data structures, data modeling, and ETL/ELT concepts
• Exposure to data pipelines, data analysis, or data engineering concepts
• Experience and exposure to some or all of the following: cloud platforms (AWS preferred; GCP or Azure helpful)
• Familiarity with data warehousing and big data tools (Snowflake, Hadoop, Spark)
• Exposure to data pipeline and orchestration tools
• Experience with APIs or distributed data systems
• Exposure to machine learning, data science, or AI‑related coursework or projects
• Familiarity with business intelligence or analytics tools

The listed annualized base pay range is: $74,000 - $111,000

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