Senior Data Engineer

15 hours ago

Hartford, Connecticut, United States The Hartford Full time
About the Role

The Hartford is seeking a Senior Data Engineer to join our Feature Integration team within Data Science Enablement organization.

This person is expected to be adaptable and a quick learner to support our Entity Resolution tech stack.

The candidate must possess strong communication skills to communicate with the business and other delivery teams.

This role will have a Hybrid work arrangement, with the expectation of working in an office (Hartford, CT, Charlotte, NC, Chicago, IL, Columbus, OH) 3 days a week (Tuesday through Thursday)

Responsibilities:
  • Accountable as a Senior Data Engineer for a large-scale data product.
  • 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.
  • Accountable for data pipeline and product physical solution designs across teams as well as tool recommendations.
  • Accountable for Data Engineering Practices across all the teams involved.
  • Implement 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.
Requirements:
  • Strong Technical Knowledge (Cloud data pipelines and data consumption products)
  • Leader and a team player with transformation mindset.
  • Ability to lead successfully in a lean, agile, and fast-paced organization, leveraging Scaled Agile principles and ways of working.
  • Guides team to mature Code quality management, DataOps principles, automated testing, and environment management practices to deliver incremental customer value.
Qualifications:
  • Bachelor's degree in computer science or related field of study
  • 5+ years of experience in Python/Pyspark
  • 5+ years in large scale big data engineering experience and designing best practices in Programming, SDLC practices, Distributed systems, Data warehousing solutions SQL and NoSQL, ETL tools, CICD, Cloud Technologies (AWS/AZURE)
  • 3+ years of developing and operating production workloads in cloud infrastructure (AWS, Azure, etc)
Preferred Qualifications:
  • Exposure to AWS best practices
  • Knowledge of core functional components/services of AWS – compute, storage, Edge, Database, Migration and Transfer, Networking, and Governance.

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