Data Engineer - Analytics

Air•Pittsburgh, PA

17h•Onsite

About The Position

Air is seeking an experienced Data Engineer to build and maintain data pipelines that deliver accurate, insightful business data. The role supports the growth of the company by sourcing data from business systems and Air’s core application, transforming it into scalable data models, and delivering insights that inform go-to-market, operations, product, and engineering decisions. The Data Engineer will collaborate with technical and business stakeholders, maintain high-confidence accuracy throughout the medallion architecture, and ensure the data tooling and models scale with the company’s growth. The role involves understanding client requirements and translating them into technical solutions; deploying and integrating software and data solutions in client environments; and designing, building, testing, and optimizing scalable data architecture. The position is full-time and based in Air’s Pittsburgh, Pennsylvania office, with up to 10% travel potentially required. U.S. citizenship is required.

Requirements

U.S. citizenship.
At least 3 years of writing, maintaining, and optimizing production-grade SQL to support business functions or applications, including CTEs, correlated and non-correlated subqueries, and window functions.
At least 3 years of data modeling experience, including knowledge of star and snowflake schemas and the distinction between dimensions and facts.
At least 3 years of experience writing ETL pipelines and using Airflow, Dagster, Prefect, or a similar orchestration tool.
1–3+ years of Python experience for pipelines, data science, or applications.
Hands-on experience in at least one startup or technology data domain: Finance, Pipeline/Funnel, Product Analytics, or Operations.
Ability to understand how end-user engagement with an application relates to conversion and revenue.
Demonstrated ability to collaborate and deliver independently.
Strong judgment and attention to detail when validating complex relationships and resolving ambiguous cases.
Excellent written communication skills, including documenting decisions with clear reasoning and auditable source support.
Ability to prioritize, triage, and execute quickly while maintaining consistent quality.
Strong stakeholder communication skills and ability to coordinate across multiple workstreams.
Careful attention to detail and data accuracy.

Nice To Haves

Current U.S. security clearance or ability to obtain one with Air’s sponsorship.
Experience in or exposure to a startup or other entrepreneurial environment.
Experience with a business intelligence tool such as Tableau, Looker, or Sigma.
Exposure to data governance practices, including source of truth, role-level security, permissions, and roles.

Responsibilities

Build and maintain data pipelines that deliver key business insights.
Source data from business systems and Air’s core application and transform it into scalable data models.
Own the execution, delivery, and validation of data pipelines supporting go-to-market, operations, product, and engineering decisions.
Collaborate with software engineers, product managers, client-facing teams, business stakeholders, and Air platform subject matter experts to understand requirements and translate them into technical solutions.
Lead deployment and integration of software and data solutions in client environments, ensuring smooth implementation and adherence to project timelines.
Design, build, and test scalable data architecture.
Write clean, testable, and maintainable code.
Participate in end-to-end software development of new feature functionality and design capabilities.
Optimize processes for speed and accuracy and seek continuous improvement.
Validate complex data relationships, resolve ambiguous cases, and maintain data accuracy.