Data Architect

ZapcomDes Moines, IA, us

job_description.job_card.variable_days_ago

serp_jobs.job_preview.job_type

serp_jobs.job_card.temporary

serp_jobs.filters_job_card.quick_apply

job_description.job_card.job_description

Job Description

Lead the assessment and redesign of our enterprise data architecture.
Deliver a current-state review and future-state design in the first 8 weeks.
Balance immediate reporting needs with long-term modernization by designing an interim architecture.
Establish an Azure-first data platform covering ingestion, storage, governance, analytics, and AI / ML workloads.
Work with business leaders to translate initiatives into project charters, ensuring quick wins as well as longer-term priorities.
Build and maintain a roadmap that phases delivery of quick wins, foundational capabilities, and advanced use cases.
Drive data governance and quality practices into day-to-day operations.
Collaborate with technical and business teams to turn data into measurable business value.

First 6–8 Weeks : Assessment & Design

Complete a review of current data architecture including sources, pipelines, reporting, and governance.

Define the target-state architecture including data lakehouse and governance design.

Develop an interim-state architecture to support ongoing reporting and analytics.

Translate business requests into clear project charters, focusing on quick wins.

Deliver a roadmap with phased delivery of near-term wins and longer-term capabilities.

8–24 Weeks : Operationalization & Quick Wins

Stand up core Azure platform components (Data Factory, ADLS Gen2, Databricks, Synapse, metadata catalog).

Roll out governance processes including data cataloging, stewardship roles, and quality measures.

Deliver short-term business solutions using interim reporting and data marts.

Turn chartered business initiatives into projects with clear outcomes.

Pilot leapfrog initiatives such as real-time analytics, AI / ML model pipelines, or self-service analytics.

6–12 Months : Scale & Transition

Expand the enterprise data lakehouse with additional curated domains.

Shift the majority of reporting and analytics from interim to target-state architecture.

Operationalize AI / ML pipelines at scale with continuous training and deployment.

Show clear improvement in data quality, governance compliance, and speed of insight.

Requirements

Strong background in enterprise data architecture, including data lakehouse design.

Hands-on knowledge of the Azure ecosystem : Data Factory, Event Hubs, ADLS Gen2, Data bricks, Synapse Analytics, Purview, Cosmos DB, Power BI, Azure ML.

Ability to translate business needs into technical solutions and formal project charters.

Experience balancing short-term requirements with future-state modernization.

Knowledge of data governance frameworks (e.g., DAMA, DCAM), metadata management, and stewardship practices.

Excellent stakeholder management and communication skills; able to bridge executives, business teams, and engineers.

Experience leading and mentoring data engineers and analysts.

8+ years of experience in data architecture / engineering with at least 3 years working on Azure platforms.

Preferred : Microsoft Azure certifications (Data Engineer Associate, Solutions Architect Expert).

Success Measures

First 6-8 Weeks

Current-state assessment and target-state design complete.

Interim architecture to support critical reporting.

Business initiatives translated into project charters.

Roadmap published.

8–24 Weeks

Foundational Azure data platform operational.

Governance processes launched.

Quick-win projects delivered.

Leapfrog pilots underway.

6–12 Months

Lakehouse expanded with curated domains.

Majority of reporting transitioned to target-state.

AI / ML pipelines in production.

Noticeable improvements in data quality and time-to-insight.

Requirements

Strong background in enterprise data architecture, including data lakehouse design. Hands-on knowledge of the Azure ecosystem : Data Factory, Event Hubs, ADLS Gen2, Data bricks, Synapse Analytics, Purview, Cosmos DB, Power BI, Azure ML. Ability to translate business needs into technical solutions and formal project charters. Experience balancing short-term requirements with future-state modernization. Knowledge of data governance frameworks (e.g., DAMA, DCAM), metadata management, and stewardship practices. Excellent stakeholder management and communication skills; able to bridge executives, business teams, and engineers. Experience leading and mentoring data engineers and analysts. 8+ years of experience in data architecture / engineering with at least 3 years working on Azure platforms. Preferred : Microsoft Azure certifications (Data Engineer Associate, Solutions Architect Expert). Success Measures First 6-8 Weeks Current-state assessment and target-state design complete. Interim architecture to support critical reporting. Business initiatives translated into project charters. Roadmap published. 8–24 Weeks Foundational Azure data platform operational. Governance processes launched. Quick-win projects delivered. Leapfrog pilots underway. 6–12 Months Lakehouse expanded with curated domains. Majority of reporting transitioned to target-state. AI / ML pipelines in production. Noticeable improvements in data quality and time-to-insight.

serp_jobs.job_alerts.create_a_job

Data Architect • Des Moines, IA, us

Job_description.internal_linking.related_jobs

serp_jobs.job_card.promoted