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- Tasks: Design and build scalable data infrastructure to support global data initiatives.
- Company: Insulet Corporation, a leader in innovative medical devices for diabetes management.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Make a real impact on healthcare with cutting-edge analytics solutions.
- Qualifications: Experience in data engineering, cloud platforms, and analytics tools like Power BI.
- Other info: Join a dynamic team dedicated to simplifying life for people with diabetes.
The predicted salary is between 36000 - 60000 £ per year.
Insulet Corporation, maker of the OmniPod, is the leader in tubeless insulin pump technology. The Analytics Engineer role focuses on designing, building, and maintaining scalable data infrastructure and analytics solutions to support global data initiatives aligned with Insulet's overall data strategy. Collaborating with senior analytics leaders and cross-functional teams, this role involves creating advanced data pipelines, optimizing data workflows, and enabling effective reporting and visualization tools. The position combines cloud infrastructure expertise, data engineering practices, and analytics development to deliver actionable insights across core business functions such as R&D, clinical, medical affairs, quality, and global manufacturing.
Responsibilities
- Design and implement robust, scalable, and efficient data pipelines for ingestion, transformation, and processing of large datasets.
- Create and maintain analytics solutions and dashboards within Power BI for dynamic reporting and data-driven decision-making.
- Work with IT and other teams to optimize data storage, retrieval, and integration using cloud platforms such as Azure, AWS, or GCP.
- Develop automation workflows for data processes, ensuring high accuracy and performance.
- Collaborate with cross-functional teams to define requirements for effective data models and architecture.
- Ensure data security, quality, and governance practices are adhered to across workflows.
- Conduct performance monitoring, debugging, and optimization of data infrastructure components.
- Partner with stakeholders to deploy and validate analytics tools, including efforts in Installation Qualification (IQ), Operational Qualification (OQ), and Performance Qualification (PQ).
- Provide documentation and training to business units on effective use of developed analytics solutions.
Technical Requirements
- Expertise in data pipeline design and development using tools like ETL frameworks, SQL, and cloud platforms such as Azure Data Factory, AWS Glue, or Google Dataflow.
- Advanced proficiency in Power BI for creating interactive dashboards and reporting solutions.
- Proficiency in scripting languages such as Python, R, or PySpark for data manipulation and automation tasks.
- Strong experience with relational databases (e.g., SQL Server, Oracle, Teradata) and exposure to NoSQL databases (e.g., MongoDB).
- Familiarity with CI/CD workflows to deploy data solutions effectively.
- Knowledge of software engineering principles and data visualization best practices.
- Functional knowledge of cloud infrastructure and distributed computing systems.
Soft Skills
- Strong analytical thinking and problem-solving skills.
- Ability to work independently and take ownership of technical initiatives while collaborating with cross-functional teams.
- Clear communication skills to articulate technical concepts to non-technical stakeholders.
- Commitment to delivering high-quality solutions that align with business goals.
- Effective documentation and training abilities to ensure adoption of analytics tools and processes.
Recommended Areas of Courses
- Data Engineering Fundamentals (e.g., ETL design, pipeline optimization).
- Cloud Platforms for Data Processing (e.g., Azure Data Factory, AWS Glue, or Google BigQuery).
- Advanced Power BI analytics techniques.
- Automation and CI/CD in data workflows.
- Data Security and Governance Practices.
- Statistical Modeling and Predictive Analytics Fundamentals.
Insulet Corporation (NASDAQ: PODD), headquartered in Massachusetts, is an innovative medical device company dedicated to simplifying life for people with diabetes and other conditions through its Omnipod product platform. The Omnipod Insulin Management System provides a unique alternative to traditional insulin delivery methods. With its simple, wearable design, the tubeless disposable Pod provides up to three days of non-stop insulin delivery, without the need to see or handle a needle. Insulet’s flagship innovation, the Omnipod 5 Automated Insulin Delivery System, integrates with a continuous glucose monitor to manage blood sugar with no multiple daily injections, zero fingersticks, and can be controlled by a compatible personal smartphone in the U.S. or by the Omnipod 5 Controller. Insulet also leverages the unique design of its Pod by tailoring its Omnipod technology platform for the delivery of non-insulin subcutaneous drugs across other therapeutic areas.
We are looking for highly motivated, performance-driven individuals to be a part of our expanding team. We do this by hiring amazing people guided by shared values who exceed customer expectations. Our continued success depends on it!
Analytics Engineer employer: Insulet
Contact Detail:
Insulet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Insulet or in the analytics field on LinkedIn. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, dashboards, and any cool projects you've worked on. This will help us stand out during interviews.
✨Tip Number 3
Prepare for those technical interviews! Brush up on your SQL, Power BI, and cloud platforms. We want to be ready to tackle any scenario they throw our way.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows we’re serious about joining the team!
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Analytics Engineer role. Highlight your expertise in data pipeline design, cloud platforms, and Power BI to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data analytics and how you can contribute to our mission at Insulet. Share specific examples of your past work that demonstrate your problem-solving skills and technical prowess.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in SQL, Python, and any cloud platforms you've worked with. We love seeing candidates who can hit the ground running with their technical know-how!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Insulet
✨Know Your Data Tools
Make sure you brush up on your knowledge of data pipeline design and the tools mentioned in the job description, like ETL frameworks and Power BI. Be ready to discuss specific projects where you've used these tools to create impactful analytics solutions.
✨Showcase Your Collaboration Skills
Since this role involves working with cross-functional teams, prepare examples that highlight your ability to collaborate effectively. Think about times when you’ve worked with IT or other departments to optimise data workflows or develop analytics tools.
✨Demonstrate Problem-Solving Abilities
Be prepared to tackle some technical questions or case studies during the interview. Practice explaining your thought process for solving complex data issues, as this will showcase your analytical thinking and problem-solving skills.
✨Communicate Clearly
You’ll need to articulate technical concepts to non-technical stakeholders, so practice simplifying your explanations. Use clear, concise language and avoid jargon when discussing your past experiences and how they relate to the role.
