ARES Enterprise

Senior Data Engineer / Data Architect | Hybrid | Camp Murray, WA | Contingent

USA

Live, first seen by us 41 days ago

Pay: Pay not listedSimilar roles state $127K–$190K
Work setting: Hybrid — work setting source
Location, Schedule & Logistics Location: Camp Murray, WA (Hybrid: ~75% telework / remote, ~25% on-site). Schedule: Monday – Friday, 06:00 AM – 2:30 PM Pacific Time.
Read the full posting
Employment: Not stated

Before you apply

Work authorization: US citizens onlyUS Citizenship required

What you’ll work on

Full posting

Design and maintain automated, fault-tolerant ETL/ELT pipelines with scheduled syncs
Cleanse, deduplicate, and curate raw feeds into a single source of truth
Architect dimensional models and star schemas in Dataverse and relational stores
Build and sustain secure REST/OData egress connections using service principals
Enforce RBAC, row-level security, and masking for PII/PHI

From the employer’s posting

design, deploy, and maintain automated, fault-tolerant ETL/ELT pipelines with scheduled synchronizations

cleanse, deduplicate, harmonize, and curate disparate raw data feeds into an authoritative single source of truth

Architect high-performance dimensional data models (Fact/Dimension tables, Star Schemas, 1:N and M:N relationships)

Build and sustain secure, automated system-to-system egress connections (REST API, OData endpoints, secure connectors)

Design and enforce enterprise-grade Role-Based Access Control (RBAC), Row-Level Security (RLS), Field-Level Security, and automated data masking/hashing for sensitive data (PII/PHI)

What you’ll bring

All qualifications

Core experience

Experience: Minimum of 3+ years of hands-on enterprise data engineering, cloud data architecture, or relational database systems design.
Data Modeling & Architecture: Demonstrated experience building dimensional models, Star Schemas, and Entity-Relationship Diagrams (ERDs) for relational repositories and downstream business intelligence tools.

Preferred experience

Familiarity with DoD/federal cloud security frameworks (e.g., IL4/IL5 boundaries, CDAO guidelines) or enterprise platforms (Advana, Army Vantage)
Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related quantitative field (or equivalent practical experience).

Qualification wording

Experience: Minimum of 3+ years of hands-on enterprise data engineering, cloud data architecture, or relational database systems design.

Data Modeling & Architecture: Demonstrated experience building dimensional models, Star Schemas, and Entity-Relationship Diagrams (ERDs) for relational repositories and downstream business intelligence tools.

Familiarity with DoD/federal cloud security frameworks (e.g., IL4/IL5 boundaries, CDAO guidelines) or enterprise platforms (Advana, Army Vantage)

Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related quantitative field (or equivalent practical experience).

Education & alternatives

- DoD Cyber Workforce / 8140 qualification or industry-standard certifications (e.g., Databricks Certified Data Engineer, Snowflake SnowPro Core, Microsoft Azure Data Engineer Associate, AWS Certified Data Engineer, CompTIA Security+). - Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related quantitative field (or equivalent practical experience).

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Posting record

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Status in our records: Live
First seen by us: Sep 24, 202641 days ago
Recorded sightings: 27
Last seen by us: Nov 4, 2026
Employer says posted: Sep 10, 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

$127K–$190K is typical

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

From 2,133 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 41

Similar jobs usually come down between day 5 and day 54.

From 10,733 similar postings that came down. Coming down is not always a hire.

ARES Enterprise is hiring

2 open jobs

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

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
AWS
Azure
Databricks
Power BI
Redshift
Snowflake
PySpark

Where the posting names them

- Data Discovery & Pipeline Engineering: Map raw, multi-source enterprise datasets; design, deploy, and maintain automated, fault-tolerant ETL/ELT pipelines with scheduled synchronizations and automated error handling. - Heavy Compute & Transformation: Utilize modern cloud compute engines (SQL, Python/PySpark, Databricks/Foundry-like environments) to cleanse, deduplicate, harmonize, and curate disparate raw data feeds into an authoritative single source of truth. - Relational & Dimensional Modeling: Architect high-performance dimensional data models (Fact/Dimension tables, Star Schemas, 1:N and M:N relationships) within Microsoft Dataverse / relational stores optimized for downstream Power Apps and Power BI.

- Enterprise Data Platform Proficiency: Proven experience developing pipelines and transformations on modern cloud data ecosystems such as Databricks, Snowflake, Palantir Foundry, AWS (Glue, EMR, Redshift), or Microsoft Azure (Synapse, Data Factory, Fabric). - Advanced Querying & Scripting: Strong proficiency in SQL and procedural data transformation languages (Python, PySpark, or equivalent). - Data Modeling & Architecture: Demonstrated experience building dimensional models, Star Schemas, and Entity-Relationship Diagrams (ERDs) for relational repositories and downstream business intelligence tools.

In this role, you will build the foundational, high-performance data backbone used by application developers and business analysts to create real-time operational apps and analytical dashboards. You will handle heavy compute transformations, build automated API egress pipelines, model clean dimensional star schemas, and enforce strict security, data quality, and role-based access controls. If you have proven experience designing and orchestrating data pipelines across commercial enterprise data platforms such as Databricks, Snowflake, Palantir Foundry, AWS, or Azure your skills will translate seamlessly to this role. Key Responsibilities

- Experience: Minimum of 3+ years of hands-on enterprise data engineering, cloud data architecture, or relational database systems design. - Enterprise Data Platform Proficiency: Proven experience developing pipelines and transformations on modern cloud data ecosystems such as Databricks, Snowflake, Palantir Foundry, AWS (Glue, EMR, Redshift), or Microsoft Azure (Synapse, Data Factory, Fabric). - Advanced Querying & Scripting: Strong proficiency in SQL and procedural data transformation languages (Python, PySpark, or equivalent).

- Familiarity with DoD/federal cloud security frameworks (e.g., IL4/IL5 boundaries, CDAO guidelines) or enterprise platforms (Advana, Army Vantage) - DoD Cyber Workforce / 8140 qualification or industry-standard certifications (e.g., Databricks Certified Data Engineer, Snowflake SnowPro Core, Microsoft Azure Data Engineer Associate, AWS Certified Data Engineer, CompTIA Security+). - Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related quantitative field (or equivalent practical experience).

Description We are seeking an experienced Senior Data Engineer / Data Architect to lead backend data transformation, pipeline engineering, and relational architecture connecting large-scale enterprise data platforms to a centralized Microsoft Dataverse / Azure environment. In this role, you will build the foundational, high-performance data backbone used by application developers and business analysts to create real-time operational apps and analytical dashboards. You will handle heavy compute transformations, build automated API egress pipelines, model clean dimensional star schemas, and enforce strict security, data quality, and role-based access controls.

- Schedule: Monday – Friday, 06:00 AM – 2:30 PM Pacific Time. - Environment: Remote work performed via secure Azure Virtual Desktop (AVD); company/contractor-provided hardware with government-issued smart card (CAC) access. Requirements

- Heavy Compute & Transformation: Utilize modern cloud compute engines (SQL, Python/PySpark, Databricks/Foundry-like environments) to cleanse, deduplicate, harmonize, and curate disparate raw data feeds into an authoritative single source of truth. - Relational & Dimensional Modeling: Architect high-performance dimensional data models (Fact/Dimension tables, Star Schemas, 1:N and M:N relationships) within Microsoft Dataverse / relational stores optimized for downstream Power Apps and Power BI. - API Integration & Egress: Build and sustain secure, automated system-to-system egress connections (REST API, OData endpoints, secure connectors) leveraging Service Principals, modern token authentication, and strict latency/uptime SLAs.

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About the role

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

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Description

We are seeking an experienced Senior Data Engineer / Data Architect to lead backend data transformation, pipeline engineering, and relational architecture connecting large-scale enterprise data platforms to a centralized Microsoft Dataverse / Azure environment.

In this role, you will build the foundational, high-performance data backbone used by application developers and business analysts to create real-time operational apps and analytical dashboards. You will handle heavy compute transformations, build automated API egress pipelines, model clean dimensional star schemas, and enforce strict security, data quality, and role-based access controls.

If you have proven experience designing and orchestrating data pipelines across commercial enterprise data platforms such as Databricks, Snowflake, Palantir Foundry, AWS, or Azure your skills will translate seamlessly to this role.

Key Responsibilities

Data Discovery & Pipeline Engineering: Map raw, multi-source enterprise datasets; design, deploy, and maintain automated, fault-tolerant ETL/ELT pipelines with scheduled synchronizations and automated error handling.
Heavy Compute & Transformation: Utilize modern cloud compute engines (SQL, Python/PySpark, Databricks/Foundry-like environments) to cleanse, deduplicate, harmonize, and curate disparate raw data feeds into an authoritative single source of truth.
Relational & Dimensional Modeling: Architect high-performance dimensional data models (Fact/Dimension tables, Star Schemas, 1:N and M:N relationships) within Microsoft Dataverse / relational stores optimized for downstream Power Apps and Power BI.
API Integration & Egress: Build and sustain secure, automated system-to-system egress connections (REST API, OData endpoints, secure connectors) leveraging Service Principals, modern token authentication, and strict latency/uptime SLAs.
Data Lineage & Quality Auditing: Implement programmatic validation routines and reconciliation scripts to audit source-versus-target records, ensuring minimal variance (<0.1%) and zero silent record drops. Maintain comprehensive documentation, including Data Dictionaries, ERDs, and version-controlled transformation lineage.
Security & Access Architecture: Design and enforce enterprise-grade Role-Based Access Control (RBAC), Row-Level Security (RLS), Field-Level Security, and automated data masking/hashing for sensitive data (PII/PHI).
Stakeholder Collaboration: Coordinate with data governance bodies, cross-functional engineering teams, and frontend developers to align data ontologies, review schemas, and resolve technical blockers.

Location, Schedule & Logistics

Location: Camp Murray, WA (Hybrid: ~75% telework / remote, ~25% on-site).
Schedule: Monday – Friday, 06:00 AM – 2:30 PM Pacific Time.
Environment: Remote work performed via secure Azure Virtual Desktop (AVD); company/contractor-provided hardware with government-issued smart card (CAC) access.

Requirements

Basic Qualifications

Experience: Minimum of 3+ years of hands-on enterprise data engineering, cloud data architecture, or relational database systems design.
Enterprise Data Platform Proficiency: Proven experience developing pipelines and transformations on modern cloud data ecosystems such as Databricks, Snowflake, Palantir Foundry, AWS (Glue, EMR, Redshift), or Microsoft Azure (Synapse, Data Factory, Fabric).
Advanced Querying & Scripting: Strong proficiency in SQL and procedural data transformation languages (Python, PySpark, or equivalent).
Data Modeling & Architecture: Demonstrated experience building dimensional models, Star Schemas, and Entity-Relationship Diagrams (ERDs) for relational repositories and downstream business intelligence tools.
API & Systems Integration: Experience engineering automated data egress pipelines via REST APIs, OData feeds, or webhooks using Service Principals and OAuth/Entra ID authentication.
Data Governance & Security: Practical working knowledge of Row-Level Security (RLS), Role-Based Access Control (RBAC), and automated data de-identification / masking for sensitive information (PII/PHI).
Clearance / Citizenship: U.S. Citizenship required. Must be eligible to obtain and maintain a favorable Federal Tier 1 (T1 / NACI) suitability background check and DoD Common Access Card (CAC).

Preferred Qualifications

Hands-on architecture experience with Microsoft Dataverse / Power Platform backend environments or Common Data Model (CDM).
Familiarity with DoD/federal cloud security frameworks (e.g., IL4/IL5 boundaries, CDAO guidelines) or enterprise platforms (Advana, Army Vantage)
DoD Cyber Workforce / 8140 qualification or industry-standard certifications (e.g., Databricks Certified Data Engineer, Snowflake SnowPro Core, Microsoft Azure Data Engineer Associate, AWS Certified Data Engineer, CompTIA Security+).
Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related quantitative field (or equivalent practical experience).

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