Job description

We’re seeking driven, curious people who bring energy to what they do and see challenges as opportunities to learn and improve. Our team of co-owners values enthusiasm, creativity, and a growth mindset, and we’re committed to putting those qualities to work on solutions that matter. If you’re ready to grow and make an impact, we’d love to be on your team. As a Senior Data Engineer you will build the enterprise data foundation that our reporting, our applications, and our AI tools all answer from. One trusted set of numbers, reconciled to the source and governed with the business. You recognize that good answers are available to us, but they take too long to assemble. Information sits across several operational systems, much of the work of pulling it together is manual, and reports built independently can answer the same question differently. That slows decisions and costs confidence in the numbers. We are solving it at the foundation rather than by adding more reports: a governed analytical platform where core business measures are calculated consistently, reconciled to the systems of record, and then made available to every consumer, including Power BI, internal applications, and AI. That work is underway. It needs a permanent technical owner, and this role will help establish the engineering practices behind the BI capability that grows around it. AWC is also preparing for a future ERP transition. The analytical foundation we build now must survive changes in our operational systems. You will help define stable business models, map legacy and future ERP data into them, and preserve trusted reporting and analytics through that transition. The ideal candidate will live within reasonable commuting distance of one of our offices in either Houston, Austin, or Dallas Texas, Baton Rouge or New Orleans Louisiana, Atlanta, Georgia, or Jacksonville Florida. This position is not eligible for visa sponsorship. How you’ll make an impact: • The analytical platform. Snowflake is our enterprise data platform. Working with the Software Architect, you will shape its data engineering architecture, environments, standards, and the patterns that everything after you is built on • Ingestion and pipelines. Bring data from our operational systems into the platform reliably and repeatably using appropriate full, incremental, or change-data patterns, with lineage and auditability built in rather than added later • Governed business models. Build canonical and dimensional models for our core business subject areas and prove they reconcile to the systems of record. Reconciliation is the gate before anything reaches a consumer, not a check we run afterward • ERP transition readiness. Help define source-to-target mappings and stable analytical contracts so legacy and future ERP data can feed the same trusted business concepts without forcing a reporting reset • Metric definitions. Work with Finance and our business owners to agree what each measure means, then encode those definitions once so every consumer gets the same answer. Business meaning is governed jointly; engineering makes it repeatable and testable • Semantic and consumption layer. Provide governed models and semantic structures that Power BI, internal applications, and AI tools can all consume. Keep reusable business logic upstream so individual reports and applications do not independently reinterpret raw system data • The standards that follow. Establish and document practical standards for modeling, pipelines, testing, deployment, lineage, access, and documentation so the next engineer builds on the foundation rather than around it What you should know going in: • You are at the beginning. This is a foundation stage. The models, standards, and patterns are still being established, and you will define them with real influence and direct support from the Software Architect who has designed the target state • Our source systems were built to run the business, not to analyze it. Structuring operational and ERP data for analysis is a meaningful part of the work, and it is the part that creates the most durable value • The source landscape will change. AWC expects a future ERP transition. The goal is not to hard-wire analytics to today's systems; it is to create governed business models and contracts that can absorb source-system change over time • Interest is ahead of capacity. Appetite for data and AI is strong and growing across our locations. Establishing a trusted, fast path to good data is an early and highly visible win • This capability grows. You will have the backing of an established, financially strong company. Resourcing expands as the work proves itself Skills you’ll need: • Experience building analytical data platforms end to end, not only maintaining someone else's. You have made the architecture and modeling decisions yourself and lived with them • Strong analytical data modeling: grain, dimensional design, slowly changing dimensions and history, late-arriving data, incremental loading, and the tradeoffs required to keep analytical models understandable and durable • Experience designing analytical models that remain stable as source systems change, including ERP migrations, source-to-target mapping, schema evolution, data contracts, or equivalent transformation work • Real depth in SQL, a modern transformation framework, and at least one cloud data platform. Snowflake experience is directly relevant, and equivalent experience elsewhere counts. Practical experience with reliable incremental loading and idempotent data pipelines matters more than tool-specific syntax • A track record of reconciling an analytical model to a financial or operational system of record, and defending it to the people who own those numbers. This is the single most relevant thing you can show us • Automated data quality testing, and the discipline to treat correctness as a release gate rather than a follow-up task • The ability to sit with a controller or a business leader, agree what a measure means, and write it down. Much of this job is definition work before it is engineering work • Comfort designing governed data access for BI, APIs, and AI consumers, including permission-aware and auditable access • Understanding of semantic-layer and BI design, with the discipline to keep shared business logic in governed models rather than recreating it independently inside dashboards Here’s what will set you apart: • Strong attention to detail and precision to ensure optimal control valve performance • Exceptional problem-solving skills, enabling effective selection of corrective actions • Proficient in interpreting schematics, drawings, and procedural instructions • Clear and effective communication skills, both verbal and written • Collaborative team player with the flexibility to work in various settings • Adaptability to work both in a shop environment and at customer-owned facilities The Rewards: • Employee Stock Ownership Plan (ESOP) • 401(K) Match • Competitive Pay • Medical, Dental and Vision Insurance Package • Employer Paid Life Insurance • Paid Time Off and Holiday Pay • Career Development Opportunities About AWC As employee co-owners, we’re driven to do more than complete tasks; we build fulfilling careers by challenging assumptions and continually raising the bar. We embrace creative, innovative approaches to deepen our expertise and deliver real value to our customers. We partner strategically with many of the world’s most recognized technology brands to help engineering, reliability, and maintenance teams solve complex problems. As experts in our partners’ technologies, we’re equipped to properly size, select, configure, and support the right solutions. Our goal is simple: combine caring, knowledgeable people with innovative technologies to help our customers succeed. How We Win Together We are committed to solving customer problems and welcome team members that want to be the trusted resource to those looking for a partner who out-knows, out-cares, and out-serves everyone else. Every day, we strive to deliver on our mission to empower people to make the greatest positive impact for the communities and families we serve together. Our Winning Together culture starts with a shared commitment to building an environment of inclusiveness, trust, and mutual respect. We know that when people like you are safe to pursue your passions, to learn, to serve, and to share in the rewards from our combined efforts, then we are winning together.

Requirements

Must-haves

The ideal candidate will live within reasonable commuting distance of one of our offices in either Houston, Austin, or Dallas Texas, Baton Rouge or New Orleans Louisiana, Atlanta, Georgia, or Jacksonville Florida.
ERP transition readiness. Help define source-to-target mappings and stable analytical contracts so legacy and future ERP data can feed the same trusted business concepts without forcing a reporting reset
The standards that follow. Establish and document practical standards for modeling, pipelines, testing, deployment, lineage, access, and documentation so the next engineer builds on the foundation rather than around it
Our source systems were built to run the business, not to analyze it. Structuring operational and ERP data for analysis is a meaningful part of the work, and it is the part that creates the most durable value
Interest is ahead of capacity. Appetite for data and AI is strong and growing across our locations. Establishing a trusted, fast path to good data is an early and highly visible win
This capability grows. You will have the backing of an established, financially strong company. Resourcing expands as the work proves itself
Experience building analytical data platforms end to end, not only maintaining someone else's. You have made the architecture and modeling decisions yourself and lived with them
Strong analytical data modeling: grain, dimensional design, slowly changing dimensions and history, late-arriving data, incremental loading, and the tradeoffs required to keep analytical models understandable and durable
Experience designing analytical models that remain stable as source systems change, including ERP migrations, source-to-target mapping, schema evolution, data contracts, or equivalent transformation work
A track record of reconciling an analytical model to a financial or operational system of record, and defending it to the people who own those numbers. This is the single most relevant thing you can show us
Automated data quality testing, and the discipline to treat correctness as a release gate rather than a follow-up task
The ability to sit with a controller or a business leader, agree what a measure means, and write it down. Much of this job is definition work before it is engineering work
Comfort designing governed data access for BI, APIs, and AI consumers, including permission-aware and auditable access
Understanding of semantic-layer and BI design, with the discipline to keep shared business logic in governed models rather than recreating it independently inside dashboards
Strong attention to detail and precision to ensure optimal control valve performance
Exceptional problem-solving skills, enabling effective selection of corrective actions
Proficient in interpreting schematics, drawings, and procedural instructions
Clear and effective communication skills, both verbal and written
Collaborative team player with the flexibility to work in various settings
Adaptability to work both in a shop environment and at customer-owned facilities
Employee Stock Ownership Plan (ESOP)
Competitive Pay
Career Development Opportunities

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aisql

Platform: ukg
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off