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 an Associate Data Engineer within Claims Data Science to design, develop, and implement modern and sustainable data assets to fuel machine learning and artificial intelligence solutions across a wide range of strategic initiatives.

As an Associate Data Engineer, you will participate in 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 will have a Hybrid work arrangement, with the expectation of working in an office location (Hartford, CT, Charlotte, NC, Chicago, IL, Columbus, OH) 3 days a week (Tuesday through Thursday).

Responsibilities:

• Participate in developing high quality, scalable software modules for next generation analytics solution suite
• Engage in activities with cross-functional IT unit stakeholders (e.g., database, operations, telecommunications, technical support, etc.)
• Participate in formulation of 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
• Participate in creating 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.
• Perform preliminary exploratory analysis to evaluate nulls, duplicates and other issues with data sources
• Assist in developing code that enables real-time modeling solutions to be ingested into front-end systems
• Produce code artifacts and documentation using GitHub for reproducible results and hand-off to other data science teams

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, IT, Management Information Systems, or a related discipline 
• 1+ years of experience in working with data
• Exposure to Python and SQL 
• Exposure to AWS Services (i.e. S3, EMR, etc)
• Exposure to ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON   
• Exposure to ETL concerning metadata management and data validation 
• Exposure to Unix and Git 
• Exposure to Automation tools (Autosys, Cron, Airflow, etc.) 
• Exposure to 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

• Candidate 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 this position.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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