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.
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.
What You’ll Do 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, BigQuery, 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
Program Experience 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
Who You Are 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.
Basic Qualifications Bachelor’s degree (expected graduation: May2027) 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
Technical Skills & Experience 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
Compensation The listed annualized base pay range is: $74,000 - $111,000
Equal Opportunity Employer Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
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