Lead Data Engineer, Benepass

• This role is ideal for someone who has successfully built or significantly scaled a data platform at a similar-stage, high-growth company and wants broad ownership as an IC
• ~5+ years of data engineering experience with increasing scope and ownership
• Strong background with AWS (RDS, Redshift, S3, Lambda, IAM) and Python
• Deep experience building and maintaining scalable ETL/ELT pipelines, data models, event schemas, and orchestration
• Strong command of SQL, warehousing concepts, dimensional modeling, and performance optimization
• You have built or significantly overhauled a data platform at a high-growth startup (e.g., Series A–C) or similar environment
• Comfortable owning the entire data ecosystem without existing mature processes or structure
• Able to translate ambiguous business questions into clear, prioritized technical work
• Experienced in partnering with non-technical stakeholders (Finance, Sales, People, Operations) who depend on timely and accurate data
• High sense of ownership and accountability for data reliability and clarity
• Bias toward action, with strong judgment on when to build for now vs. build for scale

Desirable

• Benepass is hiring a Lead Data Engineer to become the end-to-end owner of our data engineering function
• This is a foundational, hands-on, high-ownership individual contributor role where you will design, build, and scale the next generation of Benepass’s data infrastructure—pipelines, warehousing, transformations, data quality, and tooling
• This is a foundational role where you will serve as the first and primary Data Engineer at Benepass, responsible for building the platform, defining standards, and establishing the patterns that future data engineering hires will follow
• This role is focused on data engineering and platform ownership, not analytics or data science — you should identify as an engineer who builds systems, pipelines, and frameworks, not dashboards or reports
• You will partner closely with Engineering, Product, Finance, People, Sales, Operations, and the Executive Team to deliver high-quality, reliable data that powers our products, business intelligence, financial reporting, internal tooling, and decision-making
• You will partner deeply with Finance, Operations, Product, Engineering, and our Executive Team to deliver the core datasets powering revenue reporting, margin analysis, compliance workflows, customer-facing features, and internal operational tooling
• You will also work heavily with our Operations “Data” team to provide the infrastructure, workflows, and tools they need to deliver dashboards, reporting, and operational insights
• Nothing will be handed to you—you will define the roadmap, technical direction, standards, and architecture for data engineering at Benepass
• You will ensure data governance, privacy, and compliance across sensitive financial, payments, and benefits datasets and will establish testing, auditability, and monitoring practices appropriate for regulated environments
• You will design for scaling volume and complexity across millions of transactions, multi-program benefit configurations, and financial system integrations
• Serve as the primary architect and builder of our data infrastructure across our AWS stack (RDS, Redshift, S3, etc.)
• Evaluate and lead the evolution of our data stack, including decisions around warehousing, orchestration, transformations, ingestion, and observability
• Define ingestion, modeling, testing, and monitoring frameworks to ensure data is accurate, reliable, and easy to use
• Partner with Engineering, Product, Finance, People, Sales, Operations, and the Executive Team to understand data needs and deliver high-value pipelines, models, and datasets
• Support financial and people analytics, revenue and margin reporting, operational workflows, and compliance/audit needs
• Provide tooling, infrastructure, and best practices to empower the Operations Data team and other internal data consumers
• Design and implement ETL/ELT pipelines, schemas, and transformations in our AWS environment
• Debug complex data issues, especially those spanning our payments, benefits, and financial systems
• Establish standards for data reliability, testing, documentation, privacy, and governance
• Create clarity where none exists—define architectural direction, roadmap, SLAs, data contracts, and cross-team processes
• Anticipate scaling needs and prepare the platform for increased volume, complexity, and product usage
• Influence product and engineering teams on event instrumentation, schema design, and logging to ensure downstream data is structured and reliable
• While we do not plan to hire additional data engineers on this team in the next year, you will:
• Define the future data engineering team structure,
• Establish foundational patterns, tooling, and documentation, and
• Position Benepass to scale efficiently once we do grow the team