HMG America LLC is the best Business Solutions focused Information Technology Company with IT consulting and services, software and web development, staff augmentation and other professional services. One of our direct clients is looking for Technical Program Manager (Data Engineering) in Bay Area OR Seattle, WA. Below is the detailed job description.
Role - Technical Program Manager (Data Engineering)
Hire - Contract
Location - Bay Area OR Seattle, WA (Hybrid, 2 days/ week)
Job Description:
As a Technical Program Manager (TPM) in our AI & Data Practice, you will be the bridge between complex client requirements and high-performance engineering execution. You will lead the delivery of sophisticated data platforms and AI-driven solutions-ranging from Snowflake-based data engineering to Generative AI POCs using advanced search and retrieval technologies like Glean.
This is not a "project coordinator" role. We need a hands-on technical leader who understands the "how" of data movement and model implementation, ensuring that our delivery is as architecturally sound as it is on schedule.
Key Responsibilities
1. Technical Delivery & Strategy
- End-to-End Program Ownership: Lead the lifecycle of AI and Data projects from initial discovery and Proof of Concept (POC) to full-scale production implementation.
- Cross-Functional Alignment: Act as the primary translator between stakeholders (Clients/Product) and technical teams (Data Engineers/AI Researchers) to ensure technical feasibility matches business value.
- Architectural Fluency: Guide teams through the nuances of Snowflake's Data Cloud and AI integration patterns (e.g., RAG architecture, vector search, and enterprise search integration with tools like Glean).
2. Agile Operations & Execution
- Sprint Management: Own the Jira and Confluence ecosystem. You will translate ambiguous client requests into crisp, actionable epics and stories.
- Lifecycle Governance: Facilitate all agile ceremonies (Standups, Sprint Planning, Retrospectives, and Demos) specifically tailored for the iterative and often unpredictable nature of AI development.
- Dependency Management: Proactively identify and resolve technical blockers, whether they are data access issues, environment misconfigurations, or API limitations.
3. Metrics & Reporting
- Data-Driven Visibility: Develop and maintain real-time dashboards to report on program health, velocity, and budget consumption.
- AI-Specific KPIs: Go beyond standard "burndown" charts to track AI-specific success metrics such as model latency, token usage efficiency, and RAG retrieval accuracy.
- Stakeholder Communication: Provide executive-level status reports that distill complex technical risks into clear business impacts.
Technical Profile & Experience
- Experience: 5+ years of experience as a TPM, specifically within Data Engineering, Analytics, or AI/ML domains.
- Data Expertise: Deep understanding of the Modern Data Stack. You should be comfortable discussing data modeling, ETL/ELT pipelines, and cloud data warehousing (specifically Snowflake).
- AI/LLM Knowledge: Familiarity with the implementation of Large Language Models (LLMs), Enterprise Search (Glean), and the infrastructure required to support them (Vector DBs, Orchestration layers).
- Toolkit: Expert-level proficiency in Jira (Advanced Roadmaps, JQL) and Confluence.
- The "Services" Mindset: Proven ability to manage multiple client workstreams simultaneously, maintaining high quality in a fast-paced, billable environment.
Core Competencies
- Ambiguity Navigator: You can take a client's vague "I want to use AI" and turn it into a structured technical roadmap.
- Analytical Rigor: You don't just report metrics; you analyze them to predict slippage before it happens.
- Influence Without Authority: You can lead highly specialized engineers and demanding clients toward a common technical goal.
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