Company Overview: Procurement Sciences AI ( PSci.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 SAM.gov ). 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: Remote Experience Level: Mid-Senior Employment 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! #J-18808-Ljbffr Procurement Sciences
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