Senior Data Analyst

ABOUT ADVANCED ENERGY

Advanced Energy (Nasdaq: AEIS) is a global leader in the design and manufacturing of highly engineered, precision power conversion, measurement and control solutions for mission-critical applications and processes. AE’s power solutions enable customer innovation in complex applications for a wide range of industries including semiconductor equipment, industrial, manufacturing, telecommunications, data center computing and healthcare. Advanced Energy has devoted four decades to perfecting power for its global customers and is headquartered in Denver, Colorado.

 

WHY BE A PART OF ADVANCED ENERGY?

Some people say it’s like working in the best of two worlds. We operate like an agile, growing, small company – you can see your work make a difference to the company every day. Things move quickly and you can see and feel it. At the same time, we’re a global company founded in 1981 and have been publicly traded for more than 28 years. We have a strong cash position, deep trust and partnership with leading customers, a global best-in-class operations capability, and a proven leadership team. We have a track record and resources to make things happen both organically and inorganically. Being part of a nimble company with a solid foundation attracts team members that are capable, driven and like a challenge. Our employees collaborate and know how to have fun inventing, working, building and winning together. At our core, we are Advanced Energy – powering the future, together.

 

POSITION SUMMARY:        

We are seeking an analytically strong and business-savvy Senior Data Analyst to drive insight generation and decision support for our Sales and Finance stakeholders. In this role, you will partner closely with the Data Product Manager and, when needed, act as a proxy product manager, helping shape user stories, prioritize the backlog, and lead stakeholder demos. You will translate business questions into robust, trusted analytics by owning the end‑to‑end lifecycle: scoping → sourcing → modeling → visualization → storytelling → adoption. The outcome is measurable business value, faster decisions, and improved performance across revenue, margin, pipeline, bookings, and cost.

 

RESPONSIBILITIES:

• Collaborate with cross-functional teams to gather and translate business requirements into actionable data product features.

• Champion data quality and reliability: institute DQ checks, validation rules, reconciliation processes, and monitor usage/performance and proactively address data issues.

• Lead end-to-end analytics delivery for Sales & Finance initiatives—from data profiling and sourcing (e.g., ERP, CRM, pricing systems) to semantic modeling, report development, and UAT.

• Continuously improve product features based on user feedback and performance metrics.

• Advance self‑service analytics by curating governed data sets, templates, and how‑to guides; coach power users to scale insights responsible.

• Advocate for user needs and ensure customer satisfaction.

• Collaborate with architecture and solution delivery teams to ensure product designs meet business requirements.

 

WORK ENVIRONMENT:

• Location: Denver, CO.

• Standard office environment.

 

QUALIFICATIONS:

• Demonstrated ability to translate business questions into analysis plans and communicate findings with clear data storytelling that drives action.

• Experience working in agile teams (scrum/kanban), partnering with product managers, engineers, and business leaders.

• Governance mindset: comfort with data policies (definitions, quality, lineage, access), PII handling, and documentation.

 

EXPERIENCE:

• 5–8+ years in data analytics with demonstrated impact; domain experience in Sales and/or Finance in manufacturing or related industries strongly preferred.

• Expert SQL and Power BI (data modeling, DAX, performance tuning, governance).

• Hands-on experience with data engineering/analysis on Azure and Databricks (e.g., Delta Lake, PySpark or Python for analysis and data preparation).

• Strong data modeling (dimensional modeling, semantic layering) and KPI design s