Senior Data Engineer / Data Architect | Hybrid | Camp Murray, WA with Security Clearance

Ares Enterprise; Tillicum (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

Ares Enterprise is seeking an experienced Senior Data Engineer / Data Architect to lead backend data transformations and pipeline engineering connecting enterprise data platforms to a centralized Microsoft Dataverse / Azure environment.

You will build a high-performance data backbone for real-time apps and analytical dashboards, handling heavy compute and secure API egress. Strong modeling and lineage practices are required.

Qualifications

• Strong SQL and Python/PySpark for ETL/ELT transformations.
• Experience designing and orchestrating data pipelines across enterprise platforms.
• Knowledge of dimensional modeling and star schemas for analytics.
• Experience with cloud data platforms like Databricks, Snowflake, Azure, AWS is preferred.

Responsibilities

• Data Discovery & Pipeline Engineering: map multi-source data into automated ETL/ELT pipelines with fault tolerance.
• Heavy Compute & Transformation: use SQL and PySpark to cleanse and harmonize data into a single source of truth.
• Relational & Dimensional Modeling: design star schemas for analytics powering Power Apps/Power BI.
• API Integration & Egress: build secure REST API and OData endpoints for system-to-system access.
• Data Lineage & Quality Auditing: implement validation scripts to ensure data accuracy and traceability.

Skills

SQL

Python/PySpark

Databricks

Dataverse

Tools

REST API

OData

Job 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 (