Staff Analytics Engineer, Upside

• This role is ideal for someone who enjoys deep technical problem-solving, cares about quality and long-term maintainability, and is motivated by helping others work more effectively with data
• You aren’t afraid to challenge the status quo when it makes the team and business better. You learn from those around you while utilizing data to advocate for informed change
• You thrive at the intersection of systems and storytelling, not only building robust solutions but also communicating their purpose, impact and rationale, so teams can experiment, iterate, and act confidently
• You care about building resilient systems that scale. You bring a mindset of continuous improvement, and know when to invest in observability, automation, or new infrastructure to reduce toil and improve outcomes for the team and end users
• You believe that pulling quality upstream starts with engineering. You champion best practices, encourage early testing and validation, and work closely with peers to build a culture of quality from the ground up
• Have 6+ years of experience in data or analytics engineering, with a track record of owning complex, business-critical data systems end to end
• Have deep expertise in SQL and Python, particularly for transforming, testing, and orchestrating very large datasets
• Are fluent with platforms like AWS, Snowflake, dbt, and Dagster, and can design extensible patterns to be used across teams
• Experience with DevOps practices (e.g., CI/CD for data), data governance, or FinOps (cost-conscious design)
• Can break down ambiguous, cross-functional data problems and lead the implementation from design to deployment, collaborating across technical and non-technical teams
• Proactively identify opportunities to improve the analytics platform and are comfortable designing and implementing impactful, reusable solutions
• Communicate clearly across audiences, from engineers and analysts to product managers and business leaders
• Understand how to balance business value, maintainability, and platform standards in your design decisions
• Are excited about the opportunity to mentor others, set standards, and leave systems better than you found them

Desirable

• We're looking for a Staff Analytics Engineer to serve as a technical leader on the Analytics Engineering team
• In this role, you'll drive the design and implementation of foundational data products and analytics platform capabilities that power Upside’s most critical product and business use cases
• You’ll lead cross-functional workstreams, shape patterns and architecture across teams, and elevate the overall quality and impact of data work at Upside
• Design and deliver highly complex, domain-critical data products used by analysts, data scientists, and product teams to unlock new product features, ML models, and strategic decisions
• Architect scalable, extensible patterns for modeling, orchestration, and data transformation—balancing flexibility, reusability, and cost-efficiency
• Own platform evolution projects such as migrating the data platform to Snowflake Semantic Views, extending Cortex, or improving orchestration tooling for analytics workflows
• Lead technical planning and delivery across cross-functional teams, breaking down complex data initiatives into scoped, sequenced workstreams implemented by you and others
• Drive platform adoption and best practices, mentoring other engineers, building internal documentation and tooling, and raising the overall bar for analytics engineering across the company
• Influence upstream and downstream teams, partnering with engineering, product, data science, and business stakeholders to align on requirements and deliver end-to-end solutions
• Represent Analytics Engineering in technical design forums and contribute to roadmap discussions that shape the future of data at Upside
• We want our engineers to have the time and support to grow in their craft and contribute meaningfully to impactful technical decisions. Engineers are encouraged to focus deeply on their work, collaborate effectively with team members, and continuously develop their skills
• Teams are thoughtfully staffed to create a dynamic and diverse environment that enhances learning and innovation