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to join our innovative and agile data team. This role is instrumental in designing, building, and evolving a modern, scalable data platform while working in deep daily collaboration with a complementary Data Analyst.
As a senior member of the team, this position requires strong technical leadership, hands-on engineering expertise, and a customer-centric mindset. You will own core data architecture and engineering decisions while mentoring the Data Analyst and ensuring shared accountability for data quality, reliability, and delivery.
Architect, implement, and maintain scalable data solutions using Google Cloud Platform, with BigQuery as the primary analytical data store. Design, build, and optimize data pipelines using Python, dbt, and Airflow (Cloud Composer) to support analytics, reporting, and downstream integrations. Develop and maintain robust APIs and integrations in Python, enabling seamless communication between the data platform and business applications. Collaborate closely with the Data Analyst to validate data models, transformation logic, and pipeline outputs, ensuring accuracy and business alignment. Support and contribute to PowerBI semantic models and dashboards, partnering with the Data Analyst to ensure performance, usability, and trusted metrics. Act as a full-stack data professional, contributing across data architecture, ingestion, transformation, analytics enablement, visualization support, and API development. Serve as a technical mentor to the Data Analyst, providing guidance on data modeling, SQL optimization, engineering best practices, and platform design. Participate jointly with the Data Analyst in monitoring, UAT, troubleshooting, and operational support of data pipelines and reporting solutions. Build and maintain technical documentation for data architecture, pipelines, and engineering standards; Work within an agile framework alongside a dedicated Product Owner to deliver iterative, high-value data solutions. Provide proactive internal customer support and demonstrate strong customer-centric behaviors for internally developed data products and platforms.
Benefits You Can Rely On:
Health, dental, and vision insurance, HSA with employer contributions, 401(k) match, employer-paid disability coverage, and life insurance. Freestyle PTO & Work-Life Balance:
Our trust-based and freestyle time-off approach removes PTO banks and offers flexible telecommuting options. Dress for Your Day:
Whether you’re client-facing or behind the scenes, we encourage you to dress in a way that helps you feel comfortable and confident. We support continuous learning through tuition reimbursement, training opportunities, and career growth paths across FNIC. A Workplace That Cares:
Access mental health support through our EAP, virtual fitness classes, in-office gym access (Omaha), and a culture that prioritizes connection, fun, and collaboration.
Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related technical field (or equivalent practical experience). ~5+ years of professional data engineering experience, with at least 2 years in a senior or full-stack data engineering role. ~ Strong expertise with BigQuery / Google Cloud Platform, including data modeling and advanced SQL optimization. ~ Proven experience building and maintaining data pipelines using Python, dbt, and Airflow (Cloud Composer). ~ Experience supporting analytics and reporting platforms, including PowerBI semantic models and dashboards. ~ Familiarity with Azure DevOps or similar CI/CD and work management tooling. ~ Strong problem-solving skills, attention to data quality, and ownership mindset. ~ Ability to thrive in an agile, fast-moving environment with close business and technical collaboration. ~ Legal authorization to work in the United States without the need for employer sponsorship, now or in the future.
Familiarity or experience with Applied System’s Epic platform. If you’re passionate about building reliable data platforms, mentoring analytical talent, and owning end-to-end data solutions in a collaborative environment, we’d love to hear from you.
Sprachkenntnisse
- English
Hinweis für Nutzer
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