Associate Data Engineer - Tech Catalyst Program; Columbus

Tech Catalyst Program – Associate Data Engineer

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.

This is a hybrid role based in Columbus, OH.

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 with 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…