Staff Engineer Jobs in Dallas, TX
Staff Engineer jobs in Dallas are in strong demand, concentrated in Uptown, Deep Ellum, and the Las Colinas corridor across telecom, financial technology, and enterprise software. Employers actively hiring include Shield AI, GEICO, and CRUSOE. Scan the live roles below and apply to whichever ones fit.
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Job Description:
The Staff Data & Analytics Engineer, Domain Enablement is a senior, hands-on role responsible for enabling complex business domains on Shield AI’s enterprise data platform.
This person will lead discovery, scope high-value data and analytics opportunities, and deliver governed data products that make operational data more usable, trustworthy, and scalable for business decision-making. The role works across the data stack—from understanding source systems and defining integration needs through transformation, modeling, semantic design, quality controls, documentation, and business consumption.
The initial focus for this role is Supply Chain and Manufacturing, including the systems, processes, and data required to support planning, procurement, suppliers, materials, inventory, production, quality, fulfillment, cost, and program operations. Over time, the role may expand to support other complex domains as enterprise priorities evolve.
This is not a dashboard-development role. The Staff Data & Analytics Engineer will establish the domain data foundations and technical direction needed to deliver durable data products and accelerate future use cases. The ideal candidate combines strong technical depth with the ability to work directly with business partners, clarify ambiguity, and turn complex operational needs into practical, staged solutions.
What you'll do:
- Lead discovery and end-to-end enablement for complex Supply Chain and Manufacturing domains initially, with flexibility to support other priority enterprise domains as business needs evolve.
- Partner directly with Supply Chain, Manufacturing, and Operations leaders to understand business processes, decisions, source systems, reporting needs, metrics, and pain points; collaborate with Finance, Program Finance, Engineering, IT, Security, and other partners where processes, systems, or data intersect.
- Translate ambiguous business needs into clear problem statements, prioritized use cases, phased roadmaps, technical designs, and achievable delivery plans.
- Design and build governed data products across the data stack, including source-system assessment and integration requirements; Bronze, Silver, and Gold data assets; transformation logic; domain marts; curated datasets; semantic models; testing; documentation; and production-readiness controls.
- Define canonical domain concepts, grain, facts, dimensions, conformed entities, historical treatment, business rules, and reconciliation approaches for high-value operational and analytical data.
- Design and deliver governed Supply Chain and Manufacturing data models and analytical assets for concepts such as parts, materials, suppliers, purchase orders, demand, supply, inventory, work orders, production, quality, cost, and fulfillment, aligned to established enterprise patterns and standards.
- Work across ERP, PLM, MES, MRP, procurement, manufacturing, quality, inventory, supplier, finance, and operational systems to create integrated and understandable data products.
- Develop and optimize transformation pipelines using Databricks, SQL, Python, PySpark, Delta Lake, and related technologies as appropriate.
- Apply enterprise ingestion, modeling, naming, semantic, quality, documentation, lineage, and promotion standards across Bronze, Silver, and Gold layers; identify where those standards need to evolve to support complex operational domains.
- Partner with Data Engineering, Platform Engineering, and Data Governance to apply shared standards and establish the ingestion, reliability, security, access, lineage, metadata, stewardship, and quality controls needed for domain data products.
Required qualifications:
- 8+ years of experience in data engineering, analytics engineering, BI engineering, data architecture, or a blended data role.
- Demonstrated experience independently delivering end-to-end data and analytics solutions—from source-system discovery and integration through governed, business-consumable data products.
- Strong experience in at least one complex operational domain, such as Supply Chain, Manufacturing, Procurement, Planning, Logistics, Operations, Industrial, or Program Management.
- Strong dimensional modeling and semantic design skills, including facts, dimensions, grain, conformed dimensions, historical treatment, and auditable business logic.
- Hands-on production experience with Databricks, including Bronze, Silver, and Gold lakehouse patterns, Delta Lake, SQL, and Python and/or PySpark.
- Experience integrating data from complex enterprise systems, such as ERP, PLM, MES, MRP, procurement, inventory, supplier, quality, production, or financial systems.
- Ability to translate ambiguous business needs into practical delivery scopes, technical designs, and prioritized roadmaps.
- Strong communication skills and comfort partnering directly with business and technical stakeholders.
Preferred qualifications:
- Experience in aerospace, defense, aviation, autonomous systems, robotics, advanced manufacturing, industrial operations, or similarly complex and regulated environments.
- Experience supporting Supply Chain or Manufacturing capabilities such as demand planning, supply planning, procurement, supplier performance, inventory and materials management, production, quality, maintenance, repair, or fulfillment.
- Experience with systems such as SAP, Oracle, IFS, Deltek, Costpoint, PLM, MES, MRP, SCM, or comparable enterprise platforms.
- Experience integrating operational measures with Program Finance, cost, inventory valuation, forecasting, planning, or program-performance reporting.
- Experience operating in controlled, export-sensitive, government, defense, or security-sensitive environments.
Job Description:
The Staff Data & Analytics Engineer, Domain Enablement is a senior, hands-on role responsible for enabling complex business domains on Shield AI’s enterprise data platform.
This person will lead discovery, scope high-value data and analytics opportunities, and deliver governed data products that make operational data more usable, trustworthy, and scalable for business decision-making. The role works across the data stack—from understanding source systems and defining integration needs through transformation, modeling, semantic design, quality controls, documentation, and business consumption.
The initial focus for this role is Supply Chain and Manufacturing, including the systems, processes, and data required to support planning, procurement, suppliers, materials, inventory, production, quality, fulfillment, cost, and program operations. Over time, the role may expand to support other complex domains as enterprise priorities evolve.
This is not a dashboard-development role. The Staff Data & Analytics Engineer will establish the domain data foundations and technical direction needed to deliver durable data products and accelerate future use cases. The ideal candidate combines strong technical depth with the ability to work directly with business partners, clarify ambiguity, and turn complex operational needs into practical, staged solutions.
What you'll do:
- Lead discovery and end-to-end enablement for complex Supply Chain and Manufacturing domains initially, with flexibility to support other priority enterprise domains as business needs evolve.
- Partner directly with Supply Chain, Manufacturing, and Operations leaders to understand business processes, decisions, source systems, reporting needs, metrics, and pain points; collaborate with Finance, Program Finance, Engineering, IT, Security, and other partners where processes, systems, or data intersect.
- Translate ambiguous business needs into clear problem statements, prioritized use cases, phased roadmaps, technical designs, and achievable delivery plans.
- Design and build governed data products across the data stack, including source-system assessment and integration requirements; Bronze, Silver, and Gold data assets; transformation logic; domain marts; curated datasets; semantic models; testing; documentation; and production-readiness controls.
- Define canonical domain concepts, grain, facts, dimensions, conformed entities, historical treatment, business rules, and reconciliation approaches for high-value operational and analytical data.
- Design and deliver governed Supply Chain and Manufacturing data models and analytical assets for concepts such as parts, materials, suppliers, purchase orders, demand, supply, inventory, work orders, production, quality, cost, and fulfillment, aligned to established enterprise patterns and standards.
- Work across ERP, PLM, MES, MRP, procurement, manufacturing, quality, inventory, supplier, finance, and operational systems to create integrated and understandable data products.
- Develop and optimize transformation pipelines using Databricks, SQL, Python, PySpark, Delta Lake, and related technologies as appropriate.
- Apply enterprise ingestion, modeling, naming, semantic, quality, documentation, lineage, and promotion standards across Bronze, Silver, and Gold layers; identify where those standards need to evolve to support complex operational domains.
- Partner with Data Engineering, Platform Engineering, and Data Governance to apply shared standards and establish the ingestion, reliability, security, access, lineage, metadata, stewardship, and quality controls needed for domain data products.
Required qualifications:
- 8+ years of experience in data engineering, analytics engineering, BI engineering, data architecture, or a blended data role.
- Demonstrated experience independently delivering end-to-end data and analytics solutions—from source-system discovery and integration through governed, business-consumable data products.
- Strong experience in at least one complex operational domain, such as Supply Chain, Manufacturing, Procurement, Planning, Logistics, Operations, Industrial, or Program Management.
- Strong dimensional modeling and semantic design skills, including facts, dimensions, grain, conformed dimensions, historical treatment, and auditable business logic.
- Hands-on production experience with Databricks, including Bronze, Silver, and Gold lakehouse patterns, Delta Lake, SQL, and Python and/or PySpark.
- Experience integrating data from complex enterprise systems, such as ERP, PLM, MES, MRP, procurement, inventory, supplier, quality, production, or financial systems.
- Ability to translate ambiguous business needs into practical delivery scopes, technical designs, and prioritized roadmaps.
- Strong communication skills and comfort partnering directly with business and technical stakeholders.
Preferred qualifications:
- Experience in aerospace, defense, aviation, autonomous systems, robotics, advanced manufacturing, industrial operations, or similarly complex and regulated environments.
- Experience supporting Supply Chain or Manufacturing capabilities such as demand planning, supply planning, procurement, supplier performance, inventory and materials management, production, quality, maintenance, repair, or fulfillment.
- Experience with systems such as SAP, Oracle, IFS, Deltek, Costpoint, PLM, MES, MRP, SCM, or comparable enterprise platforms.
- Experience integrating operational measures with Program Finance, cost, inventory valuation, forecasting, planning, or program-performance reporting.
- Experience operating in controlled, export-sensitive, government, defense, or security-sensitive environments.
See All 308+ Staff Engineer Jobs in Dallas
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Find Staff Engineer JobsStaff Engineer Job Market in Dallas
Who's Hiring
- Shield AI150
- GEICO36
- CRUSOE14
- Bestow7
- Equinix7
Top Industries Hiring
- Media & Entertainment
- Technology & Software
- Consulting & Professional Services
Staff Engineer Jobs in Dallas: Frequently Asked Questions
How do I get a staff engineer job in Dallas?
The strongest path into a staff engineer role in Dallas is through the city's dense telecom, financial technology, and enterprise software sectors, which consistently drive the most openings. Employers in Uptown and the Platinum Corridor in Las Colinas hire heavily at this level. Candidates who can demonstrate system design ownership, cross-team technical leadership, and experience with large-scale distributed systems stand out in Dallas interviews.
Which companies hire staff engineers in Dallas?
Companies currently hiring staff engineers in Dallas include Shield AI, GEICO, and CRUSOE, per current listings on Migrate Mate as of September 2026. Dallas draws a mix of major telecom carriers, regional banks, healthcare technology firms, and global technology companies with large engineering campuses in and around the metro.
Are there remote staff engineer jobs in Dallas?
Yes, though availability depends on the role. Staff engineers focused on software architecture, platform infrastructure, or data systems tend to have more remote options than those tied to on-site hardware or embedded systems work. About 67% of staff engineer openings tied to Dallas are remote or hybrid as of September 2026. Cloud platform and backend architecture roles based out of Dallas employers are the most likely to offer fully remote arrangements.
How can I get a staff engineer job in Dallas with little or no experience?
The most realistic entry point in Dallas is through senior software engineer or principal engineer roles at mid-size technology companies in areas like Addison or Irving, where the jump to staff-level is shorter than at large enterprises. Dallas's growing fintech and healthtech scenes regularly promote from within, so joining as a senior engineer with strong system design skills and taking on cross-team projects is a proven path to the staff engineer title locally.
Which industries hire the most staff engineers in Dallas?
Most staff engineer openings in Dallas sit in Media & Entertainment, Technology & Software, and Consulting & Professional Services, per current listings on Migrate Mate as of September 2026. Dallas's position as a national headquarters hub for telecom carriers and financial institutions, combined with rapid growth in healthcare technology and defense contracting in the broader metro, makes it one of the more diversified staff engineering markets in Texas.
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