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Senior Data Engineer (AWS, Databricks)SwiftCruit • Hartford, Connecticut, United States
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Senior Data Engineer (AWS, Databricks)

SwiftCruit
  • US
    Hartford, Connecticut, United States
  • US
    Hartford, Connecticut, United States
Jetzt Bewerben

Über

Who Are We? Taking care of our customers, our communities and each other. That’s the Travelers Promise. By honoring this commitment, we have maintained our reputation as one of the best property casualty insurers in the industry for over 170 years. Join us to discover a culture that is rooted in innovation and thrives on collaboration. Imagine loving what you do and where you do it. Compensation Overview The annual base salary range for this position is a nationwide market range and represents a broad range of salaries for this role across the country. The actual salary will be determined by factors including the scope, complexity, location of the role, and the skills, education, training, credentials and experience of the candidate. Salary Range: $139,400.00 - $230,000.00 Target Openings: 1 Employees are also eligible for performance-based cash incentive awards as part of a comprehensive compensation and benefits program. What Is the Opportunity? The Travelers Data Engineering team constructs pipelines that contextualize and provide easy access to data by the entire enterprise. As a Senior Data Engineer you will accelerate growth and transformation of our analytics landscape. You will bring a strong desire to guide team members’ growth and develop data solutions that translate complex data into user-friendly terminology. You will leverage your ability to design, build and deploy data solutions that capture, explore, transform, and utilize data to support Artificial Intelligence, Machine Learning and business intelligence/insights. What Will You Do? Design and build production data pipelines across AWS, Snowflake, Databricks supporting both batch and near real-time analytics workloads. Establish reusable engineering patterns and frameworks – parameterized, modular, idempotent pipeline templates that reduce duplicated effort and inconsistent implementations. Drive down lead time from commit to production by removing manual steps, leveraging AI, building self‑service tooling, and standardizing the path to deployment; treat cycle time as a metric you actively own and improve. Champion SDLC discipline covering version control, peer code review, automated testing, environment promotion, change management, and documentation. Integrate AI coding tools into daily workflow to accelerate scaffolding, refactoring, test generation, code optimization, and documentation with measurable impact on throughput and quality. Measure and demonstrate impact, tying AI‑tool adoption to concrete outcomes such as reduced lead time, faster test coverage, and improved consistency, and share those results to drive broader adoption. Evaluate emerging tooling and make pragmatic recommendations on what engineers should adopt, standardize on, or avoid. DataOps: Blur the lines between data and software engineering practices. Employ CI/CD, automated testing, and apply trunk‑based or short‑lived branch development to data the same way it is to software. Modernize legacy workloads – help manage and optimize AbInitio pipelines and, when applicable, help migrate or re‑platform AbInitio pipelines toward cloud‑native, declarative, ELT‑based patterns on Snowflake and Databricks where it delivers value. Embed data quality, observability, and lineage into pipelines as a default – automated data tests, freshness/quality SLAs, and traceable lineage. Optimize for cost and performance across Snowflake compute, Databricks clusters, and storage, applying FinOps‑aware engineering practices. Mentor and upskill engineers through code review, pairing, design guidance, and documented standards, acting as a technical multiplier for the team. What Will Our Ideal Candidate Have? Bachelor’s Degree in STEM related field or equivalent. Ten years of related experience building, designing and operating production data pipelines at scale. Demonstrable experience architecting, designing and building scalable, secure data solutions using AWS, Databricks, Snowflake and AbInitio or similar platforms. A track record of leveraging AI assistants, creating skills/tools to augment data engineering practices throughout the development lifecycle. The ability to lead technical direction for data engineering initiatives across cloud and on‑premises infrastructure. Willingness to run mentoring sessions and offer technical guidance to the 20‑person admin team. Ability to manage infrastructure deployment and optimize cloud resources. Drive to learn, identify and set technical standards and influence engineering practices and data governance policies. Ability to lead and take action even when there is no clear owner, inspire and motivate others, and be effective at influencing team members. Technical Skills: Cloud: Proficiency with commonly used AWS services and architectures for data and analytics solutions. Databricks: Workspace management, cluster configuration, open table formats (Iceberg, Delta Lake), Unity Catalog, building and tuning Spark/pySpark/SQL workloads. Data Warehousing: Strong understanding of data modeling, dimensional modeling (star/snowflake schemas) and medallion (bronze/silver/gold) architecture. AI Coding Assistants: Familiarity using Claude Code, Codex, Copilot, Cursor, etc. for day‑to‑day engineering tasks. AbInitio: Proficiency with GDE, CoOperating System, and EME, including maintaining and optimizing existing graphs. CI/CD for data: Git‑based workflows, branching strategy, and pipeline automation (GitHub Actions, GitLab CI, or Jenkins). Infrastructure as Code: Familiarity with a configuration‑driven, repeatable approach to environments (e.g., Terraform).
What is a Must Have? Bachelor’s degree in computer science, related STEM field, or its equivalent in education and/or work experience. 6 additional years of data engineering experience on top of the bachelor’s degree. What Is in It for You? Health Insurance: Employees and their eligible family members – including spouses, domestic partners, and children – are eligible for coverage from the first day of employment. Retirement: Travelers matches your 401(k) contributions dollar‑for‑dollar up to your first 5% of eligible pay, subject to an annual maximum. If you have student loan debt, you can enroll in the Paying it Forward Savings Program. Travelers will make an annual contribution into your 401(k) account when you pay toward your student loan. A Pension Plan that is 100% funded by Travelers is also available. Paid Time Off: Minimum of 20 days PTO annually, plus nine paid company holidays. Wellness Program: Tools, discounts and resources that empower you to achieve wellness goals and caregiving needs. Includes free professional counseling services, health coaching and other resources to support daily life. Volunteer Encouragement: Matching Gift and Volunteer Rewards program enables employees to give back to the charity of their choice. Employment Practices Travelers is an equal‑opportunity employer. We value the unique abilities and talents each individual brings to our organization and recognize that we benefit in numerous ways from our differences. In accordance with local law, candidates seeking employment in Colorado are not required to disclose dates of attendance at or graduation from educational institutions. If you are a candidate and have specific questions regarding the physical requirements of this role, please send us an email so we may assist you. Travelers reserves the right to fill this position at a level above or below the level included in this posting. To learn more about our comprehensive benefit programs please visit http://careers.travelers.com/life-at-travelers/benefits/.
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  • Hartford, Connecticut, United States

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  • English
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