Data Engineer
Company: Procurement Sciences
Location: Washington
Posted on: May 24, 2025
Job Description:
Company Overview: Procurement Sciences AI () is at the vanguard
of generative artificial intelligence, transforming the government
contracting sector as a Series A rocketship, proudly backed by
Battery Ventures, a top 1% global technology leading venture
capital firm. As a venture-backed B2B SaaS entity, we are dedicated
to revolutionizing federal, state, and local business approaches to
government contracting with disruptive AI capabilities. Our team is
committed to addressing customer pain points through an AI-first
strategy, ensuring our solutions are effective and ahead of the
curve. Our flagship platform, celebrated for its "Win More Bids"
value proposition, enhances revenue streams for our clients while
driving unparalleled operational efficiencies. By harnessing the
power of generative AI, tailored for the government contracting
domain, we offer a unique competitive advantage. Our collaboration
with Battery Ventures provides the resources and support to rapidly
scale our innovations, redefining success standards and promising a
quantum leap in value generation and operational excellence for our
clients.Job Description: We are seeking a skilled Data Engineer to
join our team, focusing on building and optimizing our data
infrastructure. The ideal candidate will have experience with
modern data stack tools, cloud platforms (Azure), and strong SQL
skills.Mandatory Requirements:
- Relational Databases: Strong understanding of schema design,
normalization, indexing, and query optimization. Hands-on
experience with PostgreSQL for data modeling and optimization.
- Data Processing & Transformation: Proficiency with dbt, SQL,
and Python for data transformation and cleansing. Experience with
workflow orchestration tools such as Airflow or Azure Data Factory.
Data Integration: Experience ingesting data from various sources
(APIs, flat files, government databases like ). Familiarity with
ETL/ELT tools such as Airbyte, PyAirbyte, and metadata governance
tools like OpenMetadata.
- Cloud Platforms: Hands-on experience with Azure Data Factory,
Azure Blob Storage, and Azure Databricks. Understanding of Delta
Lake for data lakehouse management, Kubernetes as a container
orchestrator & control plane.
- Programming & Scripting: Proficient in Python for data
manipulation and automation. Strong SQL skills, including writing
complex queries with CTEs, window functions, and
optimizations.
- Version Control: Experience with Git, including branching
strategies and collaborative development.
- Soft Skills: Excellent communication skills to explain complex
concepts to technical and non-technical stakeholders. Strong
problem-solving skills and ability to troubleshoot data issues
efficiently. Ability to collaborate effectively within a team and
lead technical initiatives.Desired (Nice-to-Have) Skills:
- Columnar Databases: Experience with ClickHouse and optimization
techniques for analytical queries.
- In-Memory OLAP Databases: Familiarity with DuckDB for read-only
analytical workloads.
- Modeling Techniques: Knowledge of dimensional modeling
(star/snowflake schemas) and Data Vault approaches.
- API Integration & Event-Driven Architecture: Understanding of
OpenAPI, Kafka, and event-driven design patterns.
- DevOps/DataOps Experience: Familiarity with GitOps, CI/CD
pipelines, and infrastructure-as-code tools like Pulumi and
ARM/Bicep.
- Generative AI & Knowledge Graphs: Understanding of
Langchain/Langgraph, knowledge graphs, Model Context Protocol, and
semantic embeddings.
- Domain Knowledge: Familiarity with US government procurement
regulations (FAR, DFARS) and data sources such as
USASpending.gov.Location: RemoteExperience Level:
Mid-SeniorEmployment Type: Full-time. If you have a passion for
working with large datasets and enjoy building scalable data
solutions, we'd love to hear from you!
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Keywords: Procurement Sciences, Towson , Data Engineer, Engineering , Washington, Maryland
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