Sr. Data Engineer

About Us

At Benepass we're making benefits easy. We believe people are the most important asset to any company. Traditional one-size-fits-all benefits packages no longer cut it in today's hybrid and remote-first environment. With Benepass, companies can tailor their benefits to the unique needs of their workforce.

Through our easy-to-use and highly customizable fintech platform, People teams can implement, administer, and track the benefits that meet employees where they are. Employers design their benefits and perks plan by setting a contribution amount and eligible spend categories. Every employee has their own individual definition of wellness and needs different things to help them be their most productive, fulfilled self.

Our Mission

Helping companies reimagine how companies take care of their people.

Our Investors

We are backed by leading investors, including Centana Growth Partners, Portage Ventures, Threshold Ventures, Gradient Ventures, Workday Ventures, and Clocktower Technology Ventures. To date, the company has raised approximately $75 million in equity capital.

Articles

• Founder Story - Jaclyn Chen
• Benepass Raises $40M Series B
• Candidate Resources
• Benepass | Candidate Resource Page
• Benepass Listed on Inc. Magazine's Best Workplaces of 2023

TEAM & ROLE

Benepass is hiring a Senior Data Engineer to build and scale the data platform that powers analytics, product reporting, and operational intelligence across the company. You will work on a small, high-impact data team that owns the warehouse, pipelines, transformation layer, semantic layer, and the infrastructure that makes data accessible, trustworthy, and fast.

This is a hands-on senior IC role. You will own the architecture and implementation of data systems from the current 0→1 foundation to 1→N scale. You will partner with Product, Engineering, Customer Operations, GTM, and Finance to understand data needs, then design and build the pipelines, models, and platform capabilities that support those needs. You will take ownership of data quality, performance, cost, and the developer experience of everyone who works with data at Benepass.

Your work enables data scientists, analysts, operators, and product teams to move fast with confidence. When this role is working, data is available when teams need it, queries run fast and stay cheap, definitions are clear and versioned, and the platform scales cleanly as the business grows.

This is a force-multiplier role. You will build shared infrastructure, not one-off reports. You will balance short-term delivery with long-term architectural integrity. You will bring strong opinions on tooling, patterns, and quality, while staying pragmatic about build-vs-buy trade-offs and speed to value.

YOU WILL

• Build and Scale the Data Platform
• Own the design and implementation of Benepass's data platform: warehouse (Redshift Serverless), replication (Airbyte/DMS), orchestration, transformation (dbt), and semantic layer (Cube).
• Architect data pipelines that reliably replicate production data (Aurora/RDS, application databases) into the warehouse with correct handling of PII, multi-tenancy, and data residency constraints.
• Maintain and evolve orchestration and job scheduling infrastructure so pipelines run reliably, recover gracefully from failures, and surface clear observability when things break.
• Design the platform for performance and cost: query patterns, materialization strategies, incremental models, partitioning, and warehouse scaling/tuning.
• Make pragmatic build-vs-buy decisions; favor leverage and speed over custom solutions where mature tooling exists.
• Own Data Quality, Governance, and Correctness
• Build data quality checks, automated testing, and validation into every pipeline and model so bad data gets caught before it reaches stakeholders.
• Define and enforce patterns for data grain, slowly changing dimensions, multi-tenant access controls, and row-level security so financial and benefits data stays correct under scrutiny.
• Work with Engineering on source data contracts, instrumentation gaps, and schema evolution so upstream changes don't break downstream reporting.
• Maintain clear lineage, documentation, and metadata so people know where data comes from, what it means, and when it was last refreshed.
• Partner with Security and Compliance on data residency, encryption, access controls, and audit requirements for regulated data.
• Enable Self-Service Analytics and Product Reporting
• Design and build dbt models (staging through marts) that codify business logic, dimensional models, and metrics in version-controlled SQL.
• Author and maintain
• Cube models and measures so governed metrics serve cleanly into BI tools (Metabase, Looker, etc.), product reporting surfaces, and internal dashboards.
• Implement row-level security patterns in Cube so multi-tenant data stays isolated and access controls reflect the business model.
• Optimize for query speed: pre-aggregations, caching strategies, and materialized views that let stakeholders query large datasets interactively.
• Provide clear paths for analysts and data scientists to extend models, write safe queries, and build new reports without waiting for engineering.
• Partner Across the Company to Deliver Data Solutions
• Product & Engineering
• Work with Product to understand data needs for internal tools, customer-facing reporting, and product analytics.
• Partner with Engineering
• (Core Services, Client Apps, Platform) to instrument events, define schemas, and close gaps where product data doesn't land cleanly in the warehouse.

ABOUT YOU

A Senior Data Platform Builder

You've built data platforms from the ground up or scaled them through significant growth.

You write production-quality SQL and Python; you're fluent in modern data stacks (warehouse, orchestration, transformation, BI/semantic layers).

You have strong opinions on data modeling, testing, and quality, with pragmatism about when to cut scope and ship.

You design systems for correctness first, then performance, then cost; you care deeply about data integrity in regulated domains.

You ship incremental value while keeping long-term architecture coherent.

A Technical Leader and Force Multiplier

You operate at a senior IC level (P4): you take ownership of ambiguous problems and drive them to durable solutions.

You partner across Product, Engineering, Customer Operations, GTM, and Finance without needing a formal PM or project manager.

You mentor data scientists, analysts, and engineers; you raise the bar for how the company thinks about data.

You make build-vs-buy decisions that favor leverage and team velocity.

You communicate technical trade-offs clearly to non-technical stakeholders and advocate for platform investments that compound.

REQUIREMENTS

• 5+ years of data engineering experience, with growing ownership of platform architecture, data pipelines, and data quality.
• Strong
• SQL and
• Python
• ; experience building production data pipelines on modern data stacks.
• Hands-on experience with data warehouses
• (Redshift, Snowflake, BigQuery) and transformation frameworks ( dbt
• ).
• Experience building and maintaining data replication pipelines (CDC, DMS, Airbyte, Fivetran, or similar).
• Solid understanding of dimensional modeling
• , data grain, slowly changing dimensions, and data quality patterns.
• Experience with semantic layers or metrics platforms (Cube, LookML, MetricFlow) and how they serve governed metrics into BI tools.
• Comfort with AWS data services (RDS, S3, Redshift, DMS, Lambda) and infrastructure-as-code (Terraform preferred).
• Experience working with PII, multi-tenant data, row-level security, and compliance requirements in regulated domains (fintech, healthcare, benefits).
• Clear written and verbal communication; you can explain technical decisions to stakeholders across the company.
• Fit with a high-ownership, high-trust culture. We hire for skill and for how people work with others.
• Nice to have
• Experience with orchestration tools
• (Airflow, Dagster, Prefect, Mage).
• Real-time data, streaming pipelines, or CDC patterns (Kafka, Kinesis, Debezium).
• BI tools (Metabase, Looker, Omni, Superset, Tableau).
• Data observability and cataloging tools (Monte Carlo, Great Expectations, Atlan).
• Fintech, payments, benefits, or healthcare domains where data correctness and compliance are critical.
• Experience with Kubernetes, Docker, or containerized data workloads.
• Exposure to data science workflows: feature engineering, experimentation platforms, or ML pipelines.
• OUR TECHNOLOGY AND STACK
• AWS (Aurora/RDS, DMS, Redshift Serverless, S3, Lambda), dbt, Cube
• , Airbyte, Python, SQL, Metabase, Terraform, Docker, Kubernetes. Most of your build time will be in SQL, Python, dbt, and data infrastructure on AWS.
• ROLE LOCATION & TRAVEL
• You will be expected to attend company-wide on-site events three times per year.

What We Offer

95% coverage of medical, dental, and vision

Fantastic benefits (of course 😃), including:

• $250 WFH setup (one time)
• $500/year Learning & Development Benefit
• $150/month cell phone + internet
• $100/month Wellness
• $100/month Co-working and Commuter Benefit
• We offer several team onsites a year
• Flexible PTO

At Benepass, we are working towards reimagining how companies take care of their people. We are committed to creating an inclusive environment for all our employees and are seeking to build a team that reflects the diversity of the people we hope to serve with our revolutionary products. Benepass is proud to be an equal-opportunity employer.