Sr. Data Engineer

Company Overview:

Procurement Sciences is at the forefront of transforming the multi-billion-dollar government contracting industry with Awarded AI, our cutting-edge platform designed to help businesses excel in government sales. We simplify complex processes, drive revenue growth, and deliver real cost savings through unmatched efficiency. As a leading venture-backed SaaS company founded by seasoned GovCon experts, we are not just participants in the AI revolution; we are shaping it by solving the industry’s toughest challenges. Our “One Team, One Fight” culture values creativity, accountability, and forward-thinking, and we invite driven builders and innovators to help us develop high-performing teams. Ranked among the top 10 percent of fastest-growing SaaS companies and on a clear path to becoming a unicorn, we are seeking top talent to join our early team and play a key role in building the next great AI software company.

Job Description: We are seeking a Data Engineer to build our customer and backend pipelines. You'll work closely with our Data and AI leadership to design and implement greenfield orchestrated data systems, including data ingestion from the product and building Source of Truth customer and finance tables. In this role, you will own the design, implementation and iterative improvement of all our data and how it gets used by various cross functional teams. Your work will directly impact product performance by providing the data to build and train recommendation and search models, maintaining product data flows, and servicing the needs of finance and ops. You'll collaborate with a talented team to solve real technical problems in a fast-growing SaaS environment.

Key Responsibilities:

• Build, deploy, and maintain production data ingestion on top of our data platform.
• Design and implement feature engineering and source of truth tables for finance and product usage metrics.
• Lay the foundation for a future analytics team to empower the business to make data driven decisions and fast experimental iteration.
• Collaborate with ML and engineering teams to support the needs to train large scale models for in production use.

Ideal Candidate:

• Strong foundation in Data Engineering with production deployment experience with multiple orchestrators
• Excited about the challenge of bringing disparate data under one roof and defining the data models that will take the business to the next level
• Collaborative problem solver who thrives in startup environments with evolving requirements
• Eager to learn new technologies while leveraging proven Data Engineering practices
• 5+ years building production data pipelines with real user data at scale
• Deep SQL and Python expertise - you think in sets and write maintainable tested code
• Collaborative problem solver who thrives in startup environments with evolving requirements
• Eager to learn new technologies while leveraging proven Data Engineering practices
• 5+ years building production data pipelines with real user data at scale
• Deep SQL and Python expertise - you think in sets and write maintainable tested code

Required Experience:

• Experience with modern data stack BigQuery (or Snowflake/Redshift), dbt or similar transformation tools, orchestrators like Airflow or Dagster
• Track record of architectural thinking making design decisions that lasted and can articulate the tradeoffs
• Experience with event-driven architectures (Kafka, Pub/Sub, SQS) and streaming vs. batch tradeoffs
• Familiarity with foundation model APIs (OpenAI, Anthropic, etc.) and vector database
• GCP ecosystem familiarity: BigQuery optimization, Cloud Functions, Dataflow, Vertex AI
• Built SaaS B2B Analytics: customer health, usage metrics, churn analysis
• U.S. citizenship with the ability to pass a Federal Background Check and Identity Verification.
• Track record of architectural thinking making design decisions that lasted and can articulate the tradeoffs
• Experience with event-driven architectures (Kafka, Pub/Sub, SQS) and streaming vs. batch tradeoffs
• Familiarity with foundation model APIs (OpenAI, Anthropic, etc.) and vector database
• GCP ecosystem familiarity: BigQuery optimization, Cloud Functions, Dataflow, Vertex AI
• Built SaaS B2B Analytics: customer health, usage metrics, churn analysis
• U.S. citizenship with the ability to pass a Federal Background Check and Identity Verification.

Desired Experience:

Requirements:

• While formal education is not a strict requirement, a Bachelor's or Master’s degree in Computer Science, Engineering, or a related field is preferred.

Compensation And Benefits:

• Competitive salary with stock options in a rapidly growing, venture-backed company.
• Comprehensive health plan, ensuring you and your loved ones are well taken care of.
• Flexible work arrangements, including full remote work capabilities, to balance your professional and personal life.
• Extensive professional development opportunities, providing a fast track for career advancement.
• Notice: Background Check Required
• Competitive salary with stock options in a rapidly growing, venture-backed company.
• Comprehensive health plan, ensuring you and your loved ones are well taken care of.
• Flexible work arrangements, including full remote work capabilities, to balance your professional and personal life.
• Extensive professional development opportunities, providing a fast track for career advancement.
• Notice: Background Check Required

As part of our employment process, a background check is required. The background check may include a review of your credit history, criminal records, and employment verification, among other items. This check is conducted in compliance with the Fair Credit Reporting Act (FCRA). By applying for this position, you acknowledge and consent to this process.

Procurement Sciences is an equal opportunity employer and is committed to a diverse and inclusive workplace. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. We encourage candidates from all backgrounds to apply