Senior Data Engineer

Opendorse•Lincoln, NE

2d•Remote

About The Position

Senior Data Engineer Location Remote (US-based) or at our headquarters in Lincoln, Nebraska Overview At Opendorse , we sit on more athlete and NIL data than anyone in the industry - and we’re just getting started. As the leading platform for athlete-brand partnerships, we’ve helped more than 140,000 athletes and thousands of brands connect and thrive in the NIL era. But we know the next frontier isn’t just partnerships - it’s trustworthy, scalable data systems that power intelligence across the business. We’re hiring a Senior Data Engineer to help build and own the foundation of our data platform. This role is about turning raw, fast-moving data into reliable, well-modeled datasets that teams across Product, Analytics, Revenue, and Leadership can trust. You'll work hands-on with our modern data stack - Snowflake, Fivetran, and MSSQL – designing data models, improving reliability, and ensuring our data scales with the business. This is a senior individual contributor role for someone who wants to own domains end-to-end and raise the bar for how data is built and used.

Requirements

5+ years of experience in Data Engineering or Analytics Engineering
Deep expertise in SQL and data modeling for analytics use cases
Experience working with managed ELT tools and cloud data warehouses
Strong understanding of source-system quirks and change management (especially MSSQL)
Proven ability to design reliable, scalable data systems
Strong communication skills and a collaborative, pragmatic mindset

Nice To Haves

Think of data as a product and not just pipelines.
Care deeply about data quality, reliability, and trust.
Enjoy solving ambiguous problems and defining the right solution.
Are comfortable pushing back on unclear or low-value data requests.
Like partnering closely with analytics, product, and engineering teams.
Want ownership and accountability without people management.
Experience With (or Similar Tools)
Data Warehousing: Snowflake
Data Integration: Fivetran or similar managed ELT tools
Databases: MSSQL (or other relational OLTP systems)
Languages: SQL (advanced), Python (for transformation, tooling, or automation)
Data Modeling: Dimensional modeling, slowly changing dimensions, analytics marts
Analytics Consumption : BI tools such as Tableau

Responsibilities

Design, build, and maintain scalable data pipelines in Snowflake, from raw ingestion through analytics-ready marts.
Own data domains end-to-end, from MSSQL source systems through Fivetran ingestion and downstream consumption.
Partner with Product, Analytics, and Engineering to translate business needs into durable data models and datasets.
Proactively monitor data freshness, quality, and reliability to diagnose and resolve issues quickly.
Optimize Snowflake performance and cost through thoughtful modeling, query design, and workload management.
Manage schema changes and source-system evolution without disrupting downstream users.
Document datasets, definitions, and assumptions to improve data trust and self-service across the company.

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