Data Engineer

Flyover in Chicago•Chicago, IL

2d•$80,000 - $90,000•Remote

About The Position

The Data Engineer builds and operates Flyover’s Azure data platform, turning ticketing, point-of-sale, and other business data into trusted reporting. Initially, the role will establish the existing Azure Synapse, Azure Data Lake Storage, and Azure Data Factory platform in a new Azure environment. Following that migration, the Data Engineer will lead improvements to the platform and help evaluate Microsoft Fabric. The position is the data subject matter expert on the IT team and works closely with Finance, Revenue, and IT leaders. The role is remote-first and based in the Chicago area. On-site work is required as needed for hands-on Level 1 IT tasks, up to approximately four hours per week, as well as occasional meetings. Compensation is $80,000–$90,000 annually, with extended benefits.

Requirements

Strong SQL/T-SQL skills, including complex joins, window functions, CTEs, MERGE, and query performance tuning.
Ability to build reliable pipelines using incremental (watermark) loads, parameterized and reusable designs, retries, and alerts that notify a person when a load fails or loads no data.
Understanding of dimensional modeling, including star schemas, facts and dimensions, and grain, sufficient to design data for a shared Power BI semantic model.
Ability to explain data and trade-offs in plain language to Finance, Revenue, and IT leaders and translate their questions into well-structured data.
Self-directed approach, with the ability to own a domain and set priorities with minimal oversight while collaborating with the System Admin team and wider IT team.
Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience.
At least 3 years in data engineering, including at least 2 years building and running production Azure Data Factory pipelines.
Hands-on experience with Azure Synapse Analytics, Azure Data Lake Storage (ADLS Gen2), and Azure SQL Database.
Experience designing layered bronze, silver, and gold lakehouse or warehouse architectures on any platform.
Experience moving data from on-premises SQL Server into Azure, including use of the self-hosted integration runtime.

Nice To Haves

Microsoft Fabric experience with lakehouse, warehouse, or pipelines.
Experience building a shared Power BI semantic model with DAX measures.
Power BI report development and service administration, including workspaces, refreshes, and row-level security.
Python/PySpark experience.
Git and Azure DevOps experience.
Experience migrating a data platform between Azure environments.
Experience with transactional data from ticketing or POS systems and attraction metrics such as attendance, admissions revenue, per capita spending, or booking pace.
Experience working in a small team and wearing multiple hats.

Responsibilities

Rebuild and migrate Azure Data Factory pipelines, the Synapse workspace, Azure Data Lake Storage (ADLS Gen2), and staging Azure SQL databases into a new Azure environment, and validate migrated data against its source.
Design, build, and maintain ADF pipelines that ingest data from on-premises SQL Servers, cloud-native ticketing systems, and other sources, including incremental loads, parameterization, triggers, error handling, and alerts for pipeline failures and data freshness.
Own the lakehouse architecture across bronze, silver, and gold layers and the contents of staging Azure SQL databases, including schemas, stored procedures, loading and transformation logic, and query performance.
Improve the platform’s reliability, cost, and design after migration, and help evaluate Microsoft Fabric as a potential next step.
Build and maintain a shared Power BI semantic model for Finance, Revenue, and IT leaders, establish consistent metric definitions, build key reports, and help teams develop their own reports.
Serve as the data subject matter expert within IT by defining data standards, documenting pipelines and data definitions, and keeping pipeline code in version control.
Handle on-site Level 1 IT tasks, including hardware setup and swaps, printer and peripheral issues, and hands-on troubleshooting, for up to approximately four hours per week.
Perform other duties as assigned.