Sr. Staff Data Engineer (Hartford, CT)

Qualifications: Position requires a Bachelor’s degree in Computer Science, Engineering, or a related field of study and 5 years of experience in a software development or data engineering-related occupation. In addition, position requires 5 years of experience in each of the following: Programming; SDLC practices; Distributed systems; Data warehousing solutions, including SQL and NoSQL; and ETL tools; AND 3 years of experience in each of the following: CICD; Bigdata; Cloud Technologies, including AWS and Azure; Python or Spark; Datamesh; Datalake; Snowflake; AWS; Developing and operating production workloads in cloud infrastructure; and Software development lifecycle (SDLC), including Agile/iterative methodologies and toolsets

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:

$149,568 to $184,920

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.

Hartford Fire Insurance Company in Hartford, CT has the following opening for a Sr. Staff Data Engineer.

Summary of Duties: Serve as the subject matter expert and/or technical lead for large scale data products. Drive End-to-End solution delivery involving multiple platforms and technologies with medium-to-large complexity or oversee certain parts of very large complex implementations, leveraging ELT solutions to acquire, integrate, and operationalize data. Partner with architects and stakeholders to influence and implement the vision of the pipeline and data product architecture while safeguarding the integrity and scalability of the environment. Articulate risks and tradeoffs of technology solutions to senior leaders with translations as needed for business leaders. Maintain accountability for data pipeline and product physical solution designs across teams as well as tool recommendations. Evaluate and assess open source tools and frameworks. Maintain accountability for Data Engineering Practices across all involved teams. Research, experiment, and utilize leading big data methodologies (AWS, Hadoop/EMR, Spark, Kafka, Snowflake and Talend) with cloud/on premise hybrid hosting solutions, on a multi-team/product level. Regularly conduct market research to maintain understanding and awareness of emerging data and analytics technologies, tools, techniques, and frameworks. Evaluate, recommend, and influence all technology-based decisions for tools and frameworks for effective delivery. Telecommuting available.