Lead AI & Data Analytics Engineer - Must be government clearance eligible

Navaide•Arlington, VA

2d•$130,000 - $195,000

About The Position

We are seeking a proactive Lead AI & Data Analytics Engineer to support a federal acquisition process modernization effort. This individual will serve as the technical and functional lead for building AI-enabled analytics products using Palantir Foundry, Microsoft Power Platform, Advana, Jupiter, and Databricks. This is not a traditional dashboard developer role. The successful candidate must be a self-starter who can engage directly with business stakeholders, understand acquisition and contract writing processes, identify high-value use cases, connect data across platforms, and deliver decision-support capabilities with limited oversight. The ideal candidate will help the client move from static reporting to integrated, AI-enabled analytics that generate actionable insights, identify risk, improve visibility, and support better acquisition decision-making.

Requirements

5+ years of experience in data analytics, data engineering, platform engineering, business intelligence, AI/ML, or analytics product development.
Experience building analytics products in Palantir Foundry.
Experience working with Advana, Jupiter, or similar federal/DoD data environments.
Strong experience with SQL, Python, TypeScript/JavaScript.
Hands-on expertise with one or more modern data engineering, analytics, or data platform technologies (e.g. Databricks, Spark, Kafka, Hadoop, Snowflake, Azure Data Factory, AWS Glue, Apache NiFi, Delta Lake).
Experience integrating and transforming data from multiple sources and translating business requirements into data products, dashboards, AI use cases, and technical solutions.
Experience applying AI, machine learning, NLP, generative AI, semantic search, or natural language querying to business or operational data.
Strong understanding of data governance, data quality, access control, and responsible AI practices.
Demonstrated ability to lead use cases, manage ambiguity, and deliver results with limited oversight.
Strong client-facing communication skills and stakeholder engagement skills.
Eligible to obtain a U.S. Government clearance
Experience with Microsoft Power Platform, including Power BI; Power Apps and Power Automate.
Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, Information Systems, Mathematics, Physics, or a related technical field, or equivalent experience.

Nice To Haves

Up to 10% travel, depending on environment cutovers, stakeholder design sessions, and validation/test events.

Responsibilities

Lead the design, development, and delivery of AI-enabled analytics products supporting acquisition and contract writing operations.
Build and maintain data products, dashboards, workflows, and analytical applications using Palantir Foundry and Microsoft Power Platform.
Work within Advana and Jupiter environments to access, analyze, and connect relevant data sources to Palantir Foundry and Power Platform solutions.
Develop data pipelines, reusable data models, and analytics layers using Databricks, SQL, Python, PySpark, or similar tools.
Build and maintain ETL/ELT pipelines in Foundry’s Pipeline Builder and Code Repositories — from raw ingest through staging to curated, production-ready datasets
Design end-to-end big data architectures across cloud implementations of Foundry, including data lakes, pipelines, warehouses, and analytics platforms; apply Foundry’s open architecture principles to ensure interoperability with existing IT systems and meet organizational and compliance requirements
Integrate AI, machine learning, natural language processing, generative AI, or automated insight-generation capabilities into analytics products and workflows.
Identify, prioritize, and drive analytics and AI use cases from concept through delivery.
Partner with acquisition, contracting, program, and technical stakeholders to understand business problems and translate them into data and AI solutions.
Develop AI-enabled capabilities such as natural language querying, automated leadership summaries, risk indicators, anomaly detection, trend analysis, workload forecasting, and decision-support recommendations.
Build dashboards and reports that provide insight into contract writing activity, workload, procurement status, cycle times, data quality, system adoption, bottlenecks, and operational risk.
Support data integration across contract writing, procurement, financial, program, and operational data sources.
Validate AI-generated outputs against source data, business rules, and subject matter expert feedback.
Establish standards for data quality, governance, documentation, and responsible AI use.
Provide technical direction to junior or support-level data analytics staff.
Present findings, prototypes, dashboards, and recommendations to both technical and non-technical stakeholders.