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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Analytics Engineer - **Company:** Riot Platforms, Inc - **Location:** Austin, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Big Data, BigQuery, Business Systems, Data Centers, Information Engineering, Data Infrastructure, Data Integration, Data Structures, Data Warehousing, Dimensional Modeling, Oracle Essbase, Python (Programming Language), Project Management Software, Netsuite, Operational Data Store, Oracle (Applications), Query Optimization, Power BI, SAP (Applications), SQL Databases, Systems Integration, Tableau (Software), Scripting, Business Intelligence Development Studio, Data Ingestion, Snowflake, Grafana, Bitcoin Mining, Information Technology, Epicor ERP, Data Analytics, Operational Systems, Code Restructuring, Looker Analytics, Software Version Control, Workday, Amazon Redshift, Databricks - **Published:** June 13, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4eb33b9b74da3225 ## About the Role Do you have experience in Schema design?, * Bachelor's degree in Engineering, Computer Science, Information Technology, or a related field - equivalent experience considered. * 5+ years of experience in analytics engineering, data engineering, BI, or a related data role. * Expert-level SQL - Comfort with complex joins, window functions, CTEs, set-based logic, and query optimization across large datasets. Able to read, refactor, and tune SQL written by others. * Modern cloud data warehousing - Strong hands-on experience with at least one modern cloud warehouse (Snowflake, BigQuery, Databricks, Redshift, or similar). Snowflake experience preferred. * Dimensional modeling - Deep understanding of star/snowflake schemas, slowly changing dimensions, and scalable analytics structures. * Modern BI / semantic-layer tooling - Hands-on experience with Power BI, Tableau, Looker, Sigma, Grafana, or similar. Strong DAX or equivalent semantic-layer skills preferred. * ERP & operational data - Experience integrating data from ERP, financial, project management, or other operational systems (NetSuite, Epicor, Procore, SAP, Oracle, Workday, or similar). * Problem-solving - Strong analytical skills and the ability to work through loosely defined business questions while managing multiple priorities. * Communication - Excellent communication skills to effectively interact with both technical and non-technical stakeholders. * Cross-functional comfort - Thrives in an environment where priorities span finance, operations, and analytics. Nice to have * Experience with NetSuite Planning & Budgeting (NSPB) or other Essbase-based planning tools. * Familiarity with dbt or similar transformation frameworks * Working knowledge of Python or another scripting language for data work * Exposure to data ingestion / orchestration tooling (Fivetran, Airbyte, Airflow, Dagster, ADF, or similar). * Experience with version control and CI/CD workflows for analytics code. * Experience integrating AI into analytics and data engineering workflows. * Experience in manufacturing, construction, energy, mining, data center, or other capital-intensive industries. ## Description Riot Platforms is looking for a Senior Data Analytics Engineer to build and scale the data foundation that powers decision-making across the business. You'll own data models end-to-end, connect data across our ERP, project management, and operational platforms, and deliver reliable reporting through our BI stack - providing visibility across our Data Center, Bitcoin Mining, and Manufacturing operations. This isn't a dashboard-building role - you'll be shaping the data models, metric definitions, and reporting frameworks that business leaders depend on. If you thrive on turning complex, fragmented data into clear, trusted insight, this is a high-impact opportunity to leave a lasting mark on how Riot scales analytics. What you'll do * Build the core analytics data model - Design and maintain scalable fact and dimension models in our cloud data warehouse that support enterprise reporting and analysis. * Create a trusted reporting layer across business systems - Integrate and model data from ERP, financial, project management, and operational platforms (e.g., NetSuite, Procore, Epicor, Snowflake, Timestream) to create a consistent source of truth. * Preserve critical business context across systems - Identify where important financial or operational detail is lost in source systems or handoffs, and design data structures that retain the fidelity needed for analysis. * Establish modeling standards and analytics best practices - Help define scalable approaches to naming, structure, metric logic, testing, and maintainability across the analytics environment. * Deliver meaningful reporting and dashboards - Build and maintain dashboards and semantic models in our BI tooling that give stakeholders visibility into financial performance, project execution, and operational KPIs. * Partner directly with stakeholders to solve ambiguous problems - Translate real business questions - such as cost overruns, efficiency gaps, and project performance - into clear datasets, metrics, and reporting solutions. * Support planning and forecasting workflows - Maintain and improve planning and budgeting environments to help align planning, forecasting, and actual performance. * Standardize KPIs across teams - Work with Finance, IT, Continuous Improvement, Operations, and other functions to define, document, and govern consistent metrics across the organization. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Destigmatizing the Workplace: Building Real Inclusion](https://www.wearedevelopers.com/videos/1492-destigmatizing-the-workplace-building-real-inclusion) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)