Senior Analytics Engineer, Finance

Boston Scientific•Maple Grove, MA

19h•Hybrid

About The Position

The Finance team is seeking a Senior Analytics Engineer to join the Business Intelligence and Analytics pillar within the Global HQ FinOps team. Over the past two years, GHQ FinOps has built a strong foundation in standardized reporting, global data assets, and process excellence. As the team continues to evolve, this role will support the design, development, enhancement, and operational support of scalable enterprise financial data and analytics solutions. Working closely with Finance, IT, and business partners, the analyst will translate business needs into technical solutions, develop and maintain analytics-ready data assets, deliver scalable reporting and analytics capabilities, and contribute to initiatives that strengthen data-driven decision-making across FP&A. This role will work across the analytics stack, leveraging technologies including Snowflake, SQL, Python, and PowerBI, while applying sound data architecture, modeling, engineering, and development practices. This is a hybrid position (in office minimum three days per week) with flexibility to be based in Marlborough, MA or Mape Grove, Minnesota. You will have the opportunity to discuss your preferred working location with your Talent Acquisition Specialist. The Senior Analytics Engineer will report to the Senior Manager, Finance Analytics & Business Intelligence within the Global HQ FinOps team. This position has a high degree of collaboration amongst the Finance Forward team, as well as interaction with corporate and divisional financial planning & analysis teams. The culture of the team is collaborative, flexible, and solutions-oriented, with team members willing to contribute across broader team responsibilities.

Requirements

Bachelor's degree in Finance, Accounting, Analytics, Computer Science, Information Systems, or a related field.
3+ years of experience in analytics engineering, data engineering, business intelligence development, data analytics, or a similar technical analytics role.
Strong analytical, critical-thinking, and problem-solving skills, with experience supporting financial reporting, data analysis, or business intelligence solutions.
5+ years of experience with relational databases such as Snowflake, AWS, MS SQL, HANA, or similar platforms.
5+ years of experience using SQL and exposure to Python, VBA, or other programming/scripting languages for data analysis and automation.
Experience developing and maintaining reports and dashboards using business intelligence tools such as PowerBI or Tableau.
Proficiency in Microsoft Excel, including Power Query, and the Microsoft 365 suite.
Working knowledge of data architecture, dimensional/data modeling, ETL/ELT patterns, data transformation, data validation, and data quality best practices.
Strong written and verbal communication skills with the ability to communicate technical concepts to business users.
Detail-oriented with strong organizational and time management skills.
Ability to manage multiple priorities and work both independently and collaboratively in a fast-paced environment.

Nice To Haves

5+ years of experience in analytics engineering, data engineering, business intelligence development, data analytics, or a similar technical analytics role.
Experience supporting financial reporting, FP&A, or other finance-related analytics.
Exposure to enterprise data platforms and cloud technologies such as Snowflake, AWS, or Azure.
Experience supporting production reporting environments, troubleshooting data or reporting issues, and implementing enhancements.
Experience with development lifecycle and engineering practices such as Git/version control, CI/CD, automated testing, and deployment processes.
Basic knowledge of Finance Reporting Systems such as Oracle Hyperion/EPM Cloud, SAP, or similar ERP and financial planning systems.
Familiarity with statistical analysis, forecasting techniques, or predictive analytics.
Exposure to automation, machine learning, or generative AI technologies is a plus.
Experience working in Agile or Scrum delivery environments; Agile certification is a plus.
Demonstrated ability to prioritize competing work, meet deadlines, and maintain a high level of accuracy and customer service.
Demonstrated curiosity, continuous learning mindset, and ability to adapt to new technologies and evolving business needs.

Responsibilities

Design, develop, test, deploy, and maintain scalable financial data and analytics solutions that enable planning, forecasting, close, performance management, and business decision-making.
Translate business requirements and complex analytical needs into well-designed technical solutions.
Develop and maintain data transformations, reusable datasets, and analytics-ready data assets using Snowflake, SQL, Python, and related technologies.
Apply engineering best practices to create solutions that are scalable, maintainable, performant, and reliable.
Design and maintain reporting datasets, dimensional data models, semantic layers, and transformation logic.
Apply data architecture and modeling best practices to ensure financial data is structured consistently and can be effectively reused across reporting and analytical use cases.
Develop and enhance dashboards, reports, semantic models, and analytical applications using Power BI and related technologies, with an emphasis on performance, scalability, usability, and consistent business logic.
Partner with Finance and business stakeholders to understand business processes, identify opportunities, define requirements, and translate business problems into technical designs and data solutions.
Apply critical thinking to challenge assumptions, clarify requirements, and recommend solutions that address underlying business needs.
Identify and apply AI capabilities, including Snowflake Cortex, to solve business problems, improve decision-making, and drive process efficiencies.
Provide operational support for Finance data and BI solutions by monitoring performance, troubleshooting data pipelines and reporting issues, resolving production defects, supporting scheduled refreshes, and ensuring reliable delivery of analytics products.
Integrate, transform, reconcile, and validate data from financial and enterprise systems including Snowflake, AWS, MS SQL, SAP, HANA, Oracle Hyperion/EPM Cloud, and related platforms to ensure data accuracy and completeness.
Develop and execute data validation, reconciliation, and testing approaches.
Maintain technical documentation, data definitions, transformation logic, and solution designs to support governance, maintainability, reporting accuracy, and established controls.
Evaluate enhancement requests, identify opportunities to simplify and modernize existing solutions, and contribute to standards and best practices for analytics engineering, development, testing, deployment, documentation, and data governance.
Contribute to team initiatives, participate in technical design discussions, share knowledge and development practices, support project delivery, and stay current on analytics engineering, cloud data platforms, BI technologies, and Finance analytics best practices.