Back to jobs

Data Platform Architect

Pay
Pay not listedSimilar roles state $154K–$226K
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-Time
From the employer’s posting

Before you apply

Work authorization
Citizens onlyTop Secret clearance required with eligibility for SCI

What you’ll work on

Full posting
  • Guide teams moving notebook prototypes into reliable production workflows

  • Set technical standards for pipelines, testing, metadata, and documentation

  • Build reusable templates and reference architectures for delivery teams

  • Guide CI/CD and MLOps practices for jobs, models, and data products

  • Advise on Spark optimization and resolve production performance issues

From the employer’s posting
Guide the transition of prototypes and notebook-based solutions into reliable, maintainable production workflows.
Establish and maintain technical standards for project structure, code organization, pipeline design, workflow orchestration, testing, metadata, lineage, documentation, and platform implementation.
Develop reusable templates, reference architectures, and implementation patterns that improve consistency and accelerate delivery.
Guide CI/CD implementation for jobs, pipelines, notebooks, packaged code, models, and data products.
Advise teams on Spark optimization, workload design, workflow dependencies, storage and compute utilization, and other platform-performance considerations.

What you’ll bring

All qualifications

Core experience

  • 5+ years of technical experience, including 3+ years designing or implementing production solutions on Databricks, Palantir Foundry, or similar modern data platforms.
  • Strong experience with Python, SQL, PySpark, and Spark SQL for scalable data-processing workflows.
  • Experience with Palantir Foundry or comparable enterprise analytics platforms, including pipeline development, governed data delivery, lineage, and operational analytics.
  • Experience designing and operationalizing data pipelines, transformation workflows, and data products supporting structured and unstructured data.
  • Hands-on knowledge of Databricks platform capabilities such as Delta Lake, Workflows, MLflow, Unity Catalog, or similar platform-native services.
  • Familiarity with DataOps, DevOps, and MLOps practices, including CI/CD, version control, testing, deployment, monitoring, and operational support.

Preferred experience

  • Experience implementing solutions in Palantir Foundry, including data-pipeline organization, governed data assets, operational workflows, and integrations.
  • Experience with Git-based CI/CD pipelines, infrastructure and deployment tooling, and cloud-native platform services.
  • Experience supporting the ML lifecycle, including model packaging, registration, deployment, monitoring, and inference-workflow integration.
  • Knowledge of enterprise data integration, API-based data exchange, and secure cross-platform interoperability.
Qualification wording
5+ years of technical experience, including 3+ years designing or implementing production solutions on Databricks, Palantir Foundry, or similar modern data platforms.
Strong experience with Python, SQL, PySpark, and Spark SQL for scalable data-processing workflows.
Experience with Palantir Foundry or comparable enterprise analytics platforms, including pipeline development, governed data delivery, lineage, and operational analytics.
Experience designing and operationalizing data pipelines, transformation workflows, and data products supporting structured and unstructured data.
Hands-on knowledge of Databricks platform capabilities such as Delta Lake, Workflows, MLflow, Unity Catalog, or similar platform-native services.
Familiarity with DataOps, DevOps, and MLOps practices, including CI/CD, version control, testing, deployment, monitoring, and operational support.
Experience implementing solutions in Palantir Foundry, including data-pipeline organization, governed data assets, operational workflows, and integrations.
Experience with Git-based CI/CD pipelines, infrastructure and deployment tooling, and cloud-native platform services.
Experience supporting the ML lifecycle, including model packaging, registration, deployment, monitoring, and inference-workflow integration.
Knowledge of enterprise data integration, API-based data exchange, and secure cross-platform interoperability.

Benefits in the posting

Full benefits wording
  • 401k matching
  • PPO and HDHP medical/dental/vision insurance
  • Complimentary life insurance
  • Generous PTO and 11 days of holiday leave
  • Onsite gym facility and trainer
  • Commuter Benefits Plan
  • In-office Cold Brew Coffee

From the employer’s posting.

About Expression

Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, AI/ML, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community.

In the employer’s words · Read in context

Apply at Expression

Posting record

Report an error
Status in our records
Live
First seen by us
Aug 19, 202683 days ago
Recorded sightings
50
Last seen by us
Nov 11, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$154K–$226K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,100 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 83

Up longer than most. Similar jobs usually come down between day 8 and day 57.

From 9,102 similar postings that came down. Coming down is not always a hire.

Expression is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • Databricks
  • Delta Lake
  • MLflow
  • Power BI
  • Spark
  • Tableau
  • PySpark
Where the posting names them
- 5+ years of technical experience, including 3+ years designing or implementing production solutions on Databricks, Palantir Foundry, or similar modern data platforms. - Strong experience with Python, SQL, PySpark, and Spark SQL for scalable data-processing workflows. - Experience with Palantir Foundry or comparable enterprise analytics platforms, including pipeline development, governed data delivery, lineage, and operational analytics.
Expression is seeking an experienced Data Platform Architect to provide architectural guidance, technical standards, and operational support for teams delivering secure, scalable data, analytics, and AI/ML solutions in mission environments. The Data Platform Architect will work across engineering, data science, analytics, platform, and mission teams to guide implementation in Databricks and Palantir Foundry. This role will help delivery teams structure data pipelines, data products, analytics and ML workflows, and platform assets so solutions are consistent, reusable, governed, supportable, and production-ready. The successful candidate will provide hands-on guidance spanning data integration, DataOps, DevOps, MLOps, governance, security, compliance, performance optimization, and platform operations while helping teams move solutions from prototypes into reliable production environments.
Key Responsibilities - Provide hands-on architectural guidance to teams implementing data pipelines, analytics workflows, data products, and AI/ML capabilities in Databricks and Palantir Foundry. - Guide selection and implementation of platform-native capabilities for data ingestion, transformation, orchestration, model execution, analytics, and data-product delivery.
- Guide selection and implementation of platform-native capabilities for data ingestion, transformation, orchestration, model execution, analytics, and data-product delivery. - Advise teams on appropriate use of Databricks, Foundry, and integrated cross-platform architectures. - Guide the transition of prototypes and notebook-based solutions into reliable, maintainable production workflows.
- Establish operational practices for deployment, environment promotion, monitoring, alerting, rollback, release management, observability, lineage, and data-quality validation. - Promote reproducible MLOps practices for model training, validation, packaging, registration, deployment, monitoring, batch inference, and lifecycle management using MLflow, Databricks workflows, and related capabilities. - Design scalable ML inference approaches supporting production workloads and establish monitoring for model performance, data drift, and system health.
- Support self-service ML capabilities that enable data scientists to efficiently deploy and monitor models. - Define integration patterns for onboarding data sources, managing schema evolution, and connecting Databricks and Foundry with enterprise systems, applications, data warehouses, streaming platforms, APIs, and BI tools. - Guide implementation of secure access controls, governed data sharing, metadata management, data catalogs, lineage, traceability, and audit-ready workflows.
Required Qualifications - 5+ years of technical experience, including 3+ years designing or implementing production solutions on Databricks, Palantir Foundry, or similar modern data platforms. - Strong experience with Python, SQL, PySpark, and Spark SQL for scalable data-processing workflows.
- Experience designing and operationalizing data pipelines, transformation workflows, and data products supporting structured and unstructured data. - Hands-on knowledge of Databricks platform capabilities such as Delta Lake, Workflows, MLflow, Unity Catalog, or similar platform-native services. - Familiarity with DataOps, DevOps, and MLOps practices, including CI/CD, version control, testing, deployment, monitoring, and operational support.
Preferred Qualifications - Deep Databricks expertise, including medallion architecture, Delta optimization, workload tuning, cluster and job strategy, and production ML enablement. - Experience implementing solutions in Palantir Foundry, including data-pipeline organization, governed data assets, operational workflows, and integrations.
- Identify and help resolve architecture, integration, reliability, and performance issues affecting production jobs, data products, and operational analytics. - Design data models supporting machine learning, analytics, and business intelligence requirements, including integrations with Tableau, Power BI, and Qlik Sense. - Build and support integrations with MAVEN Smart Systems/Palantir Foundry environments and other enterprise systems.

Your next step

Complete your application on expression-networks.breezy.hr. The employer’s form will show what is required.

Applying through Breezy HR

  • No account needed.

Already applied? Track this application

Demand for Data Leadership roles

New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.

Weekly new Data Leadership postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 781, the most 1,203, and the latest week had 890.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

Expression is seeking an experienced Data Platform Architect to provide architectural guidance, technical standards, and operational support for teams delivering secure, scalable data, analytics, and AI/ML solutions in mission environments.

The Data Platform Architect will work across engineering, data science, analytics, platform, and mission teams to guide implementation in Databricks and Palantir Foundry. This role will help delivery teams structure data pipelines, data products, analytics and ML workflows, and platform assets so solutions are consistent, reusable, governed, supportable, and production-ready.

The successful candidate will provide hands-on guidance spanning data integration, DataOps, DevOps, MLOps, governance, security, compliance, performance optimization, and platform operations while helping teams move solutions from prototypes into reliable production environments.

Clearance: Top Secret clearance required with eligibility for SCI.
Location: Full time onsite at the Suffolk Building, 5616 Columbia Pike, Falls Church, VA

Key Responsibilities

  • Provide hands-on architectural guidance to teams implementing data pipelines, analytics workflows, data products, and AI/ML capabilities in Databricks and Palantir Foundry.
  • Guide selection and implementation of platform-native capabilities for data ingestion, transformation, orchestration, model execution, analytics, and data-product delivery.
  • Advise teams on appropriate use of Databricks, Foundry, and integrated cross-platform architectures.
  • Guide the transition of prototypes and notebook-based solutions into reliable, maintainable production workflows.
  • Establish and maintain technical standards for project structure, code organization, pipeline design, workflow orchestration, testing, metadata, lineage, documentation, and platform implementation.
  • Develop reusable templates, reference architectures, and implementation patterns that improve consistency and accelerate delivery.
  • Promote scalable approaches including medallion architecture, governed data publishing, reusable transformation logic, and shared analytics and ML components.
  • Conduct technical reviews and provide actionable guidance to improve scalability, maintainability, reliability, and supportability.
  • Guide CI/CD implementation for jobs, pipelines, notebooks, packaged code, models, and data products.
  • Establish operational practices for deployment, environment promotion, monitoring, alerting, rollback, release management, observability, lineage, and data-quality validation.
  • Promote reproducible MLOps practices for model training, validation, packaging, registration, deployment, monitoring, batch inference, and lifecycle management using MLflow, Databricks workflows, and related capabilities.
  • Design scalable ML inference approaches supporting production workloads and establish monitoring for model performance, data drift, and system health.
  • Support self-service ML capabilities that enable data scientists to efficiently deploy and monitor models.
  • Define integration patterns for onboarding data sources, managing schema evolution, and connecting Databricks and Foundry with enterprise systems, applications, data warehouses, streaming platforms, APIs, and BI tools.
  • Guide implementation of secure access controls, governed data sharing, metadata management, data catalogs, lineage, traceability, and audit-ready workflows.
  • Establish data-quality standards and automated testing approaches for analytical and ML workloads.
  • Partner with stakeholders to define data definitions, business logic, governance requirements, and compliant handling of structured and unstructured data.
  • Advise teams on Spark optimization, workload design, workflow dependencies, storage and compute utilization, and other platform-performance considerations.
  • Identify and help resolve architecture, integration, reliability, and performance issues affecting production jobs, data products, and operational analytics.
  • Design data models supporting machine learning, analytics, and business intelligence requirements, including integrations with Tableau, Power BI, and Qlik Sense.
  • Build and support integrations with MAVEN Smart Systems/Palantir Foundry environments and other enterprise systems.
  • Collaborate with engineers, data scientists, BI analysts, product managers, platform and security teams, and mission stakeholders to align architecture decisions with delivery priorities.
  • Participate in design sessions, technical reviews, sprint activities, demonstrations, and cross-team problem solving.
  • Maintain technical documentation supporting implementation consistency, reuse, operational handoff, and long-term supportability.

Required Qualifications

  • 5+ years of technical experience, including 3+ years designing or implementing production solutions on Databricks, Palantir Foundry, or similar modern data platforms.
  • Strong experience with Python, SQL, PySpark, and Spark SQL for scalable data-processing workflows.
  • Experience with Palantir Foundry or comparable enterprise analytics platforms, including pipeline development, governed data delivery, lineage, and operational analytics.
  • Experience designing and operationalizing data pipelines, transformation workflows, and data products supporting structured and unstructured data.
  • Hands-on knowledge of Databricks platform capabilities such as Delta Lake, Workflows, MLflow, Unity Catalog, or similar platform-native services.
  • Familiarity with DataOps, DevOps, and MLOps practices, including CI/CD, version control, testing, deployment, monitoring, and operational support.
  • Strong understanding of data quality, metadata management, lineage, access control, and governance within secure or regulated environments.
  • Experience troubleshooting architecture, integration, performance, and operational issues across distributed data platforms.
  • Ability to establish technical standards, guide architecture and implementation decisions, and clearly communicate technical concepts to technical and non-technical stakeholders.

Preferred Qualifications

  • Deep Databricks expertise, including medallion architecture, Delta optimization, workload tuning, cluster and job strategy, and production ML enablement.
  • Experience implementing solutions in Palantir Foundry, including data-pipeline organization, governed data assets, operational workflows, and integrations.
  • Experience with Git-based CI/CD pipelines, infrastructure and deployment tooling, and cloud-native platform services.
  • Experience supporting the ML lifecycle, including model packaging, registration, deployment, monitoring, and inference-workflow integration.
  • Knowledge of enterprise data integration, API-based data exchange, and secure cross-platform interoperability.
  • Experience with Advana/MAVEN Smart System (Palantir Foundry) or similar DoD enterprise analytics environments.
  • Prior experience supporting Department of Defense, Intelligence Community, or other Federal mission environments.

Benefits:

Expression offers competitive salaries and benefits, such as:

  • 401k matching
  • PPO and HDHP medical/dental/vision insurance
  • Education reimbursement up to $10,000/yr
  • Complimentary life insurance
  • Generous PTO and 11 days of holiday leave
  • Onsite gym facility and trainer
  • Commuter Benefits Plan
  • In-office Cold Brew Coffee

About Expression:

Founded in 1997 and headquartered in Washington DC, Expression provides data fusion, data analytics, AI/ML, software engineering, information technology, and electromagnetic spectrum management solutions to the U.S. Department of Defense, Department of State, and national security community. Expression’s culture focuses on creating immediate and sustainable value for our clients via agile delivery of tailored solutions built through constant engagement with our clients. Expression was ranked #1 on the Washington Technology 2018's Fast 50 list of fastest-growing small business Government contractors and a Top 20 Big Data Solutions Provider by CIO Review.

We make sure to provide everyone with the tools and opportunities to grow while working on some of the newest technologies in the industry. We get excited about celebrating our professionals' milestones, accomplishments, promotions, overcoming challenges, and many other aspects that make an engaging collaborative environment.

Equal Opportunity Employer/Veterans/Disabled
Expression is an Equal Opportunity Employer. If you require a reasonable accommodation during the application or interview process, please submit your request to our Human Resources department through the application portal.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay

No pay amount identified in the saved description.

Location & working pattern

Falls Church, VA

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.