Sr Data Engineer

Hasbro•Boston, MA

19h

About The Position

We are growing our Enterprise Data & Engineering team! Do you have a passion for data and a drive to build things that matter? We’re looking for a Senior Data Engineer to join our high-visibility Enterprise Data & Engineering team, helping Hasbro better reach consumers with compelling products and entertainment. This is an impactful role for a technically strong engineer who excels at designing and delivering production-grade data solutions independently and as a collaborative partner! In this role, you will take ownership of complex data pipelines, transformations, and analytics infrastructure that power decision-making across the business. You’ll work closely with data scientists, analytics engineers, and business partners, contributing deep technical expertise to modern cloud data platforms and code-based engineering practices. We believe great data engineering is a craft, and we’re building a team that takes that seriously.

Requirements

4–7 years of hands-on experience in data engineering or a closely related field.
Strong hands-on expertise with Databricks and cloud data platforms such as Azure and/or AWS.
Deep proficiency in SQL, data modeling, and Python for data pipeline development, transformation logic, and automation.
Solid experience with version control using GitHub (or a comparable platform), including branching strategies, pull requests, and code review workflows.
Proven ability to deliver end-to-end data products, from build through production deployment and ongoing support.
Experience with code-first orchestration tools (e.g., Databricks Asset Bundles, Airflow, or similar); familiarity with Databricks Asset Bundles (DABs) is a plus but not required.
Familiarity with or curiosity about AI-enabled development tools (such as Claude Code, Codex, Cursor, or similar coding assistants) and an interest in leveraging them to write better code, accelerate development, and improve engineering workflows.
Working knowledge of data governance fundamentals, including data quality, metadata, and lineage.
Understanding of CI/CD principles and automated testing in data pipeline development.
Strong written and verbal communication skills, with the ability to work effectively across technical and non-technical teams.
Bachelor’s or master’s degree in Computer Science, Information Systems, or a related field, with equivalent experience accepted.

Nice To Haves

Experience with DBT (data build tool) is a strong plus — particularly around testing, writing modular and reusable transformations, and optimizing how data models are built and maintained.

Responsibilities

Design, build, and optimize scalable data pipelines, transformations, and data models that underpin analytics and data products.
Own end-to-end delivery of data engineering initiatives, from technical design and planning through production rollout and ongoing support.
Write and tune complex SQL queries and Python-based pipeline code to support analytics, reporting, and data modeling needs.
Drive engineering best practices across the team, including version-controlled development via GitHub (or equivalent), CI/CD, automated testing, observability, and documentation.
Lead data architecture and design decisions for new and evolving data products, ensuring solutions are scalable, well-governed, and performant.
Collaborate with data scientists, analytics engineers, and business partners to understand data needs and deliver high-quality, consumable data products.
Support data quality monitoring and validation efforts, ensuring accuracy, completeness, and reliability across data products.
Develop and apply data governance principles, including metadata management and data lineage.
Contribute to code reviews, technical documentation, and a culture of engineering excellence.