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

ARES Enterprise
Washington, USA
Full Time, Contract
Senior · 3+ years experience
Hybrid
Discovered 2 weeks ago
Microsoft DataverseMicrosoft AzureDatabricksSnowflakePalantir FoundryAWS

Full Job Posting

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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