The Hartford is seeking a Data Engineering Manager within Claims Performance Analytics to lead a team of Data Engineers to design, develop, and implement modern and sustainable data assets to fuel analytics solutions across a wide range of strategic initiatives.  

As a Data Engineering Manager, you will lead and mentor a small 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, MLOPs, 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 can have a Hybrid or Remote work arrangement.  Candidates who live near one of our office locations  will have the expectation of working in an office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise. 

Responsibilities: 

• Lead and mentor 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  

• Prototype high impact innovations, catering to changing business needs, by leveraging new technologies 

• Consult with cross-functional stakeholders in the analysis of short and long-range business requirements and recommend innovations which anticipate the future impact of changing business needs 

• Formulates logical statements of business problems and devises, tests and implements efficient, cost-effective application program solutions 

• Identify and validate internal and external data sources for availability and quality. Work with SMEs to describe and understand data lineage and suitability for a use case 

• Create data assets and build data pipelines that align to modern software development principles for further analytical consumption. Perform data analysis to ensure quality of data assets 

• Produce code artifacts and documentation using GitHub for reproducible results and hand-off to other data science teams 

Qualifications: 

• 5+ years of relevant experience recommended 

• Bachelor’s degree in Computer Science, Engineering, IT, MIS, or a related discipline  

• Experience in managing Data Engineering initiatives in an Agile environment  

• Proficiency in Python and SQL  

• Proficiency in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON    

• Proficiency in ETL concerning metadata management and data validation  

• Proficiency in Unix and Git  

• Proficiency in Automation tools (Autosys, Cron, Airflow, etc.)  

• Experience with AWS Services (i.e. S3, EMR, etc) a plus  

• Experience with Cloud data warehouses, automation, and data pipelines (i.e. Snowflake, Redshift) a plus  

• Experience with DVT is 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