Associate Data Engineer - Tech Catalyst Program (Columbus)

The Hartford•Columbus, OH

1d•$74,000 - $111,000•Hybrid

About The Position

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.

Requirements

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
Foundational experience with at least one programming language (Python, Java, or R)
Foundational understanding of data structures, data modeling, and ETL/ELT concepts
Foundational exposure to data pipelines, data analysis, or data engineering concepts

Nice To Haves

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 AI-related coursework or projects
Familiarity with business intelligence or analytics tools
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

Responsibilities

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
Develop solutions using cloud-native data platforms (AWS, with GCP exposure for AI capabilities)
Work with modern tools such as Snowflake, BigQuery, and cloud storage solutions
Support data platform engineering, automation, and pipeline orchestration
Contribute to data modernization initiatives, including migration to cloud environments
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
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
Participate in a 10-week immersive onboarding and technical training experience
Engage in continued capability-building focused on modern data engineering, cloud, and AI
Gain hands-on delivery and exposure through placement on Agile, product-aligned teams supporting enterprise data solutions
Experience business-critical use cases across insurance and analytics domains
Receive mentorship, coaching, and peer learning designed to accelerate development
Build a strong internal network and long-term career path