Data Engineer

The Hartford•Charlotte, NC

8d•Hybrid

About The Position

The Hartford is seeking a Data Engineer within the Actuarial Strategic Modeling(ASM) team 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 a 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.

Requirements

2+ years of relevant experience recommended
Bachelor’s degree in Computer Science, Engineering, IT, Management Information Systems, or a related discipline
Experience in R (preferred), Python, and SQL
Experience in ingesting data from a variety of structures including relational databases, Hadoop/Spark, cloud data sources, XML, JSON
Experience in ETL concerning metadata management and data validation
Experience in Linux and Git
Experience in Automation tools (Autosys, Cron, Airflow, etc.)
Exposure to AWS Services (i.e. S3, EMR, etc) a plus
Able to communicate effectively with both technical and non-technical teams
Able to translate complex technical topics into business solutions and strategies

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, technical support, etc.)
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.
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.