Director of Data Engineering, Data Science Team

Dir Data Engineering - GE06AE

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 Director of Data Engineering within Global Specialty Data Science & Analytics  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, as well as business intelligence assets and other analytic work across a wide range of strategic initiatives.

 

As a Director of Data Engineering, you will lead a 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, AIOPs, 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 arrangement, with the expectation of working in an office location (Charlotte NC, Chicago IL, Columbus OH or Hartford CT) 3 days a week (Tuesday through Thursday).  

 

Responsibilities:

• Actively lead and develop a team of 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
• Collaborate with Data Scientists and Product Owners to advise approaches to business opportunities
• Develop the design and vision for data pipelines and testing frameworks, both batch and real-time to meet business needs while balancing maintainability, reliability, security, and scalability.
• Provide guidance on and independently navigate data warehouses, understand data architectures, and join disparate data sources to ensure quality and appropriateness of data solutions.
• Lead the use and development of GitHub best practices for version control, documentation, and code collaboration throughout the data science lifecycle and ensure solutions align with best practices
• Contribute to and execute a multi-year roadmap to build and remediate enterprise-grade data assets leveraging cloud-based target state technology and architecture
• Drive disciplined innovation by balancing a relentless focus on delivering results and customer adoption with out-of-the-box thinking and a continuous improvement mindset
• Coordinate activities with cross-functional IT unit stakeholders (e.g., database, operations, telecommunications, technical support, etc.)

Qualifications:

• 8+ years of relevant experience recommended
• Bachelor’s degree in Computer Science, Engineering, IT, MIS, or a related discipline
• Experience in managing Data Engineering teams in an Agile environment
• Experience designing and delivering scalable data engineering solutions that integrate GenAI capabilities and agentic AI systems
• Expertise in Python and SQL 
• Expertise in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON   
• Expertise in ETL concerning metadata management and data validation 
• Expertise in Unix and Git 
• Expertise in Automation tools (Autosys, Cron, Airflow, etc.) 
• Experience with AWS Services (i.e. S3, EMR, etc.) or GCP 
• Experience 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

Candidates 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