Senior Data Product Engineer

RigUp•Austin, TX

About The Position

RigUp is the source-to-pay solution built for energy. By combining purpose-built software with expert teams, we empower the world’s leading energy companies and their suppliers to work better, together. Learn more about how RigUp is equipping everyone in the energy ecosystem to operate with greater speed and efficiency at rigup.com The Senior Data Product Engineer is a full-stack data professional who owns a Data Product from end-to-end, from data ingestion and pipeline design to final business insight. The role involves partnership with internal and external stakeholders across Engineering and Business teams, and the individual serves as a subject matter expert, delivering high-quality, scalable data solutions and insights. Sitting at the intersection of data engineering and product management, the Senior Data Product Engineer combines hands-on technical expertise with strategic vision, driving value-focused data product development and innovation. Why Join Us? Our Data team is on a mission to turn data into products that drive real impact across the business. We’re passionate about building reliable, scalable data solutions that help teams make better decisions and move faster. If you thrive in a dynamic environment, enjoy partnering closely with engineers and business leaders, and are excited about owning data products from end to end we’d love to hear from you.

Requirements

Bachelor’s degree in a technical field or equivalent practical experience
5+ years of years of proven experience in business analytics, data engineering, or comparable data roles
Expert proficiency in SQL/Python with a proven ability to aggregate, gather, and manipulate data, and contribute to data pipeline building
Demonstrated knowledge and experience working with large and disparate data sets, including data collection processes, data modeling, data analysis, and writing reports on findings of the research
Significant experience with creating & presenting management dashboards and reports in data visualization/business intelligence tools (e.g. Sigma, Tableau, PowerBI, HEX, Jupyter notebooks, etc.)
Experience with data modeling, and contributing to data pipelines
Effective communication skills, both written and verbal, as well as the ability to develop concise and effective presentations tailored to specific audiences at all levels of the organization
Strong organizational, planning, quantitative and analytical skills; strategic and creative thinking with keen business judgment, focus, and ability to see the "big picture"
Comfort in a dynamic, fast-moving, Agile, and matrix work environment
Regular, on-time attendance
Ability to travel 10% of the time
Ability to communicate effectively
Ability to use office equipment such as a computer, copier and telephone
Ability to use office computer programs such as e-mail, Google Docs, Microsoft Word, PowerPoint and Excel
Constantly remaining in a stationary position, often standing or sitting for prolonged periods
Ability to manipulate office equipment such as a computer, copier and telephone

Nice To Haves

Experience with Scrum or Kanban development methodologies
Experience with utilizing code repositories (ie. GitHub)
Exposure to advanced analytics techniques, ie. machine learning

Responsibilities

Proactively manages stakeholder relationships across business and technical teams, regularly synthesizing feedback and needs into actionable technical plans
Lead the design, development, and optimization of robust, scalable data pipelines for efficiency, speed, and cost
Build and refine star schemas and advanced data models (e.g., using dbt) to establish authoritative sources of truth
Deliver analytic “data apps” and light integration/data capture solutions as needed to meet evolving organizational priorities
Develop impactful data visualizations, dashboards, and reusable analytics to enable deep-dive insights and “why” analysis
Proactively engage with managers, directors, and business stakeholders to clarify ambiguous problems, capture requirements, and align on solution approaches
Own projects from discovery through delivery within a specific business or technical domain, ensuring solutions align with the analytics and data product strategy
Conduct user interviews and gather stakeholder feedback to deeply understand business needs; translate them into actionable features, datasets, or analytic products
Collaborate with Data Product & Engineering leadership to identify major problem areas and opportunities, driving improvements that enhance company-wide data availability, speed, and quality
Assess and evaluate new feature requests or technical initiatives using impact, effort, and business value frameworks; drive prioritization based on expected outcomes
Define and track adoption and success metrics for delivered data products; iterate based on usage data and direct stakeholder feedback
Mentor junior engineers and lead cross-functional project teams, elevating both data engineering and product practices
Empower business users by coaching them in self-service analytics, troubleshooting complex issues, and advancing data literacy across the organization
Stay current with evolving industry trends, technologies, and approaches in end-to-end data engineering and analytics; contribute recommendations to evolve internal methods
Champion user perspectives within engineering, and represent technical constraints or opportunities to business stakeholders while balancing feasibility and impact
Regularly present product updates and project outcomes to both technical and non-technical audiences, ensuring alignment and transparency
Model and promote company standards for data quality, stewardship, and product enablement in all team initiatives