Data Architect Engineer

Tria Federal (Tria); Washington (District of Columbia); On-site; USD 150,000 - 190,000; Full time

Job summary

Tria Federal seeks a Senior Data Architect Engineer to join the DIA O&I Enterprise Integration and Assessments Data Team, accelerating dataset understanding and delivering ML/data solutions. The role moves from dataset inventory to actionable models, selecting methods and tools suited to mission problems, emphasizing responsible ML and reproducible workflows.

You will work on-site at DIA HQ in Washington, DC, collaborating with government leads and stakeholders while maintaining security and

Qualifications

• B.S. in related field with 5+ years of experience, or 10+ years with no B.S.
• Must be a U.S. Citizen
• Active TS/SCI w/ CI Poly Clearance
• Senior-level experience in ML, data science, data architecture, or data engineering
• Strong Python and SQL experience
• Experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow
• Experience assessing datasets for ML readiness including data quality, metadata, labeling, and feature engineering
• Experience building reproducible technical workflows and documenting implementation approaches
• Experience using AWS SageMaker for experimentation and deployment

Responsibilities

• Independently assess and explain datasets, including content, structure, quality, gaps, lineage, metadata, constraints, and known limitations
• Identify what is needed to make datasets ML-ready, including labeling, ground truth, feature creation, and data quality considerations
• Recommend practical approaches for addressing bias, drift, and model limitations
• Design, build, and iterate ML models appropriate to the data and use case, such as classification, entity or record matching, anomaly detection, and NLP, as applicable
• Establish baselines and define evaluation metrics tied to operational utility
• Perform error analysis to guide model improvements and inform recommendations
• Build reproducible workflows that can be rerun and sustained within the customer’s operating environment and security constraints
• Support implementation decisions, including batch versus real-time processing, resource and cost tradeoffs, and latency or throughput considerations
• Use AWS SageMaker for experimentation and execution, including notebooks or Studio, training jobs, processing jobs, pipelines or automation, model registry, and deployment approaches as permitted
• Provide clear technical recommendations to the team and Government lead on data strategy, modeling choices, architecture patterns, and implementation plans
• Proactively identify technical risks, opportunities, and recommended paths forward with minimal oversight

Skills

Python

SQL

Machine Learning

Data Architecture

Data Engineering

AWS SageMaker

Spark/PySpark

Model Evaluation

Stakeholder Communication

Reproducible Workflows

Education

B.S. in related field

Tools

Spark

PySpark

TensorFlow

Scikit-learn

Git

Jupyter Notebooks

Model Registry

Job description

Who We Are

Tria Federal delivers digital services and technology solutions that support the health and safety of veterans, service members and civilians. For two decades, federal agencies have relied on Tria companies to advance their critical missions and modernize their systems, so that they can uphold their commitment to the American people. Today, we are pushing the boundaries of possibility through partnerships and investments in artificial intelligence and emerging technologies, developing solutions for the biggest challenges that government will face tomorrow.

We are proud to employ and support military veterans who bring mission-first mindset, technical expertise, and leadership qualities that strengthen our work. Veterans, transitioning service members, and military spouses are strongly encouraged to apply.

Job Description

A Senior Data Architect Engineer to support the DIA O&I Enterprise Integration and Assessments Data Team, focused on accelerating dataset understanding and delivering fit-for-purpose machine learning and data solutions.

The role will help the team move from “what data do we have and what can it support?” to “what model or workflow should we implement, and how do we sustain it?” The emphasis is on selecting the right method or tool for the mission problem, including determining when ML is appropriate and when rules, heuristics, or simpler analytics are better suited.

Basic Requirements

• B.S. in related field with 5+ years of experience or 10+ years with no B.S.
• Must be a U.S. Citizen
• Must have an ACTIVE TS/SCI w/ CI Poly Clearance
• Senior-level experience supporting machine learning, data science, data architecture, or data engineering efforts
• Strong Python and SQL experience
• Experience with common machine learning frameworks and libraries, such as scikit-learn, PyTorch, or TensorFlow
• Experience assessing datasets for ML readiness, including data quality, metadata, labeling, ground truth, feature engineering, and constraints
• Experience designing, building, evaluating, and improving ML models based on mission or business use cases
• Experience defining model evaluation metrics and conducting error analysis
• Experience building reproducible technical workflows and documenting implementation approaches
• Experience using AWS SageMaker for experimentation, training, processing, pipelines, model registry, or deployment approaches
• Sound software engineering practices, including Git, readable and modular code, basic testing, documentation, and reproducibility
• Ability to work independently, provide technical recommendations, and interface with Government leads and senior stakeholders with limited oversight
• Familiarity with scalable data processing tools such as Spark or PySpark is a plus

Responsibilities

• Independently assess and explain datasets, including content, structure, quality, gaps, lineage, metadata, constraints, and known limitations
• Identify what is needed to make datasets ML-ready, including labeling, ground truth, feature creation, and data quality considerations
• Recommend practical approaches for addressing risk considerations such as bias, drift, and model limitations
• Design, build, and iterate ML models appropriate to the data and use case, such as classification, entity or record matching, anomaly detection, and natural language processing, as applicable
• Establish baselines and define evaluation metrics tied to operational utility
• Perform error analysis to guide model improvements and inform recommendations
• Build reproducible workflows that can be rerun and sustained within the customer’s operating environment and security constraints
• Support implementation decisions, including batch versus real-time processing, resource and cost tradeoffs, and latency or throughput considerations
• Use AWS SageMaker for experimentation and execution, including notebooks or Studio, training jobs, processing jobs, pipelines or automation, model registry, and deployment approaches as permitted
• Provide clear technical recommendations to the team and Government lead on data strategy, modeling choices, architecture patterns, and implementation plans
• Proactively identify technical risks, opportunities, and recommended paths forward with minimal oversight

ACTIVE TS/SCI with CI POLY CLEARANCE REQUIRED* MUST BE U.S. CITIZEN

Work Location: ON-SITE SUPPORT DIA HQ in Washington D.C.

Why Tria?

What defines the Tria brand is more than just our dedication to excellence in our craft; it’s our incredible team of dedicated, talented, and passionate people that make Tria so exceptional. As people powering possible, we are all partners in our team’s shared success.

As a company that cares about people, we seek to cultivate a culture in which all can thrive personally and professionally. We offer a top-tier benefits package to invest in your physical, mental, and financial health and wellness so that you can be your best self - at work and in life. At Tria, we are growth-minded, entrepreneurial in spirit, and committed to fostering a culture of inclusion and opportunity for all. Whatever your background, your role, your department, or stage in your professional journey, here you will have opportunities to learn new skills, seize new challenges, and advance your career as we grow.

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