Manager, Data Operations - Acton, Mass. or San Diego, CA (Hybrid)

Insulet Corporation•San Diego, CA

1d•Hybrid

About The Position

Insulet Corporation, maker of the OmniPod, is the leader in tubeless insulin pump, transforming the lives of people with diabetes through innovation. We are seeking a Data Engineering Manager to lead our Data Engineering Platform team in building and maintaining the world class Data and AI platform. Join a fast-paced, mission-driven medical device company where data plays a critical role in improving patient outcomes and operational excellence. As a Manager , Data Engineer , you’ll lead a team of talented data engineers responsible for designing, building and delivering secure, scalable data platform serving directly to our internal and external stakeholders in Commercial, Sales, Marketing, Market Access, Product launches and several other initiatives. This role involves directly working with the other Engineering Leads and cross-functional teams on exciting, high-impact projects that shape the future of our products and data platform. You’ll be a key contributor organizing and helping the team with managing the backlog of work items building in collaboration with technical leads and stakeholders for our Databricks-based data infrastructure, ensuring it meets the rigorous standards of the medical device industry. This is a unique opportunity to blend technical expertise with product ownership, helping to drive innovation. We offer a dynamic and collaborative work environment, where your attention to detail and passion for quality will directly influence product development, clinical insights, and operational efficiency. If you're looking for a role where your work truly matters—and where you’ll grow alongside a team of talented engineers and healthcare professionals—this is the place for you.

Requirements

Bachelors degree in Mathematics, Computer Science, Electrical and Computer Engineering, or a closely related STEM field is required
10+ years of Data Engineering, Software Engineering development experience.
3+ years of experience leading Data Engineering development teams.
Experience in data quality assurance, control and lineage for large datasets in relational/non-relational databases
Experience managing robust ETL/ELT pipelines for big real-world datasets that could include messy data, unpredictable schema changes and/or incorrect data types
Experience with both batch data processing and streaming data
Experience in implementing and maintaining Business Intelligence tools linked to an external data warehouse or relational/non-relational databases is required
Demonstrated leadership in enterprise data literacy and data architecture
Demonstrated knowledge in SQL/relational and noSQL databases is require
Demonstrated knowledge of managing large data sets in the cloud (Azure/AWS SQL, Databricks, etc) is required
Demonstrated knowledge of building, maintaining and scaling cloud architectures (Azure, AWS, etc), specifically cloud data tools that leverage Spark, is required
Demonstrated coding abilities in Python, Java, C or scripting language
Demonstrated familiarity with different data types as inputs (e.g. CSV, XML, JSON, etc)
Demonstrated knowledge of database and dataset validation best practice
Ability to communicate effectively and document objectives and procedures

Nice To Haves

Master’s degree in Mathematics, Computer Science, Electrical and Computer Engineering, or a closely related STEM field; or a BS with experience working with data technologies, is preferred
Experience in medical device, healthcare, or manufacturing industries is desirable
HIPAA experience a plus
Knowledge of ETL and workflow tools (Databricks workflows, Azure Data Factory, AWS Glue, etc) is a plus

Responsibilities

Lead and mange a scrum team of Data Engineers (local and remote)
Drive the development of new and novel data architectures and pipelines and lead technical discussions to align stakeholders on the technical approach using Databricks.
Work with cross functional stakeholders to accomplish data integrations, approvals, validation and deployment
Mentor and coach engineers fostering growth and promoting best practices
Work with IT, analytics and cross functional teams to identify data sources, determine data collection and design aggregation mechanisms
Perform data quality checks and data clean up
Interface with business stakeholders in cross-functional teams, including manufacturing, quality assurance, and post-market surveillance in order to understand various applications and their data sets
Develop data preprocessing tools as needed
Maintenance and understanding of the various business intelligence tools used to visualize and report team analytics results to the company
Ensure all data processes comply with FDA, ISO 13485, HIPAA, and other relevant medical device regulations.
Collaborate with Quality Assurance and Regulatory Affairs teams to align data practices with audit and documentation standards.