Data Engineer - Analytics
Air · Pittsburgh, Pennsylvania, United States · Presencial · Greenhouse
Esta vacante está restringida a candidatos en: EE. UU.. Ciudad: Pittsburgh. Modalidad: Presencial
Sobre el empleo
We are seeking an exceptional and experienced Data Engineer team member, a role for someone who shares our passion and obsession with shipping insightful and accurate data. You will be a core member of our team dedicated to helping drive our growth by building and maintaining data pipelines that deliver key business insights. The ideal candidate is an analytically minded engineer with large dataset experience. You must also possess strong interpersonal skills to work cross-functionally across internal teams and with Air platform Subject Matter Experts (SMEs).
You will support the proliferation of our enterprise data by sourcing data from business systems and our core application, and transforming that into a scalable data model delivering key insights. This role involves collaborating with technical and business stakeholders, maintaining high-confidence accuracy across every stage of our medallion architecture, and ensuring our tooling and data model scales to meet growth. You will own the execution, delivery, and validation of key data pipelines driving GTM, Operations, Product, and Engineering decisions.
This role is a full-time position located out of our office in Pittsburgh, PA.
This role may require up to 10% travel
Scope of Responsibilities- Collaborate with other software engineers, product managers, and client-facing teams to understand client requirements and translate them into technical solutions
- Lead the deployment and integration of our software and data solutions in client environments, ensuring smooth implementation and adherence to project timelines
- Actively participate in designing, building and testing scalable data architecture
- Craft clean, testable, and maintainable code
- Participate in the end-to-end software development of new feature functionality and design capabilities
- Optimize processes for maximum speed and accuracy
- Regularly seek out innovation and continuous improvement, finding efficiency in all assigned tasks
- U.S. Citizenship is required
- 3+ years of writing, maintaining, and optimizing Production grade SQL to support business functions and/or applications. Knows how to efficiently write CTE’s, correlated and non-correlated subqueries, and window functions.
- 3+ years of data modeling. Knows star and snowflake schemas and the difference between a dimension and a fact.
- 3+ years writing ETL pipelines. Has used Airflow, Dagster, Prefect, or similar orchestration tools.
- 1-3+ years of Python for pipelines, data science, or applications
- Has hands-on experience in at least one startup/tech data domain: Finance, Pipeline/Funnel, Product Analytics, Operations
- Ability to quickly understand how end user engagement with an application ties to conversion and revenue.
- Demonstrated track record of working collaboratively and delivering independently
- Strong judgment and attention to detail when validating complex relationships and resolving ambiguous cases
- Excellent written communication — able to document decisions with clear reasoning and auditable source support
- Ability to prioritize, triage, and execute quickly while maintaining consistent quality
- Strong stakeholder communication skills and the ability to coordinate across multiple workstreams
- Close attention to detail and validating data accuracy
- Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
- Experience in or exposure to the nuances of a startup or other entrepreneurial environment
- Experience with a Business Intelligence tool (Tableau, Looker, Sigma, etc.)
- Exposure to Data Governance practices (Source of Truth, Role Level Security, permissions and roles)
Postulación
Publicado hace 6 horas
Recurso para miembros · Ver planes
Recuerda: Vagaslume.Tech no cobra tasas, cursos ni pagos por participar en procesos de selección. Si recibes algún cobro relacionado con la contratación, no realices el pago.