> Markdown version of [/jobs/ext/4413447-data-platform-engineer](https://www.wearedevelopers.com/jobs/ext/4413447-data-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Platform Engineer - **Company:** EAGLE RIVER INC - **Location:** Vail, CO, United States - **Experience:** Expert - **Salary:** $108,805.0 - $163,197.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), ArcGIS (Software), Big Data, Information Systems, Databases, Continuous Integration, Customer Data Management, Data Infrastructure, Extract Transform Load (ETL), Data Migration, Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), Microsoft Data Access Components, Meter Data Management (Flow Meters), Microsoft SQL Server, Operational Databases, Performance Tuning, Windows PowerShell, Power BI, Simple Data Format, SQL Stored Procedures, SQL Server Integration Services, Systems Integration, Transact-SQL, Microsoft Power Automate, Azure Data Factory, Gitlab, Git, Data Lakes, Information Technology, Software Version Control, Data Pipelines, Ssas Tabular - **Published:** October 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=8faf9b4071245af8 ## About the Role * Bachelor's degree in Information Systems, Computer Science, or a related technical field, or two (2) additional years of relevant professional experience. * Five (5) or more years building and operating production data pipelines (seven (7) years without a degree), including T-SQL and SQL Server database design and performance tuning, SSIS and/or Azure Data Factory, Python (pandas or similar), and Azure data services. * Hands-on system-to-system integration experience (file exchange, APIs, or database-to-database) * At least one major system replacement or data migration, including profiling, mapping, conversion, and reconciliation * Git-based version control * Ability to document and explain technical trade-offs clearly. Preferred Qualifications * Utility, municipal, or public-sector experience, especially with a customer information or billing system, Cityworks, or Esri ArcGIS. * Experience with SCADA historian data (iHistorian or similar) or AMI meter data. * PowerShell, Power BI semantic models, and CI/CD for data pipelines. * PowerShell scripting. * Power BI and an understanding of how semantic models consume data. * SSAS Tabular, data lake, or other Microsoft data platform experience beyond SQL Server and Data Factory. * CI/CD for data pipelines or database projects. ## Description * DATA PIPELINES: Design, build, and maintain ETL/ELT pipelines on SQL Server, SSIS, and Azure Data Factory that feed the District's central data environment. Build the schemas, views, stored procedures, and incremental extract patterns that keep large datasets current without full reloads. Monitor load jobs, troubleshoot failures to root cause, and set up alerting, data quality checks, and documentation so problems are caught before users notice and others can support the pipelines. * INTEGRATIONS: Engineer and maintain data interfaces between our CIS and vendors such as payment processing, meter data management, and bank file exchange, including file formats, schedules, validation, and exception handling. Build and support connections among the CIS, Cityworks, Esri ArcGIS, operational historian data, and financial systems. Evaluate API, file, and database options with vendors, recommend the durable approach, and design integrations that limit exposure of customer data. * SYSTEM REPLACEMENTS: Serve as data lead on upcoming replacements, starting with CIS and finance. Profile source data, define mappings, build and run conversion pipelines, and reconcile results. Build the staging environments and validation reporting that prove a migration before go-live, support cutover, and rebuild downstream pipelines as source systems change. * PLATFORM OPERATIONS: Automate data tasks with Python, PowerShell, and Power Automate, and manage pipeline code and database objects in GitLab under the team's change practices. Administer the Azure data services the platform runs on. Deliver curated, well-documented datasets to the analytics team: you own the pipelines, and they own the semantic models and reports.