Data Engineer - Hybrid

Data Engineer - GE08AE

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 Data Engineer within Global Specialty 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.

This role will have a Hybrid work arrangement, with the expectation of working in an office location (Charlotte NC; Hartford, CT; Chicago, IL; Columbus, OH; San Antonio, TX; Lake Mary, FL) 3 days a week (Tuesday through Thursday).

Must be eligible to work in the US without company sponsorship

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.)

• 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.

Qualifications:

• 2+ years of relevant experience recommended.

• Bachelor's degree in computer science, Engineering, IT, Management Information Systems, or a related discipline

• Experience in 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 Unix and Git

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

• Exposure to AWS Services (i.e., S3, EMR, etc.) a plus

• 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.

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:

$97,600 - $146,400

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

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