1h 44m ago
Sr. Director Data Engineering and Operations - Erlanger, KY
On-site
|United States of AmericaSr. Director Data Engineering and Operations - Erlanger, KY
Archer Daniels Midland | Agribusiness
1h 44m agoOn-site
Full Time
Lead
United States of America
Sr. Director Data Engineering and Operations - Erlanger, KY
Role Summary
The Head of Data Engineering & Operations leads data engineering as a capability at ADM: the talent, engineering standards, and delivery quality of the data engineers who work inside data product and digital product teams. You are one of the builders of the enterprise data foundation, working in partnership with Platform & Architecture and the Product teams. Engineers from the ADM Capability Center (ACC) are part of the team from day one.
Operations sits within this role, including the managed-services partner relationship. You will lead its integration into the product model, so that running data products and building them are owned together rather than by a separate organization.
Key Responsibilities
Scope & Parterships
Qualifications
Role Summary
The Head of Data Engineering & Operations leads data engineering as a capability at ADM: the talent, engineering standards, and delivery quality of the data engineers who work inside data product and digital product teams. You are one of the builders of the enterprise data foundation, working in partnership with Platform & Architecture and the Product teams. Engineers from the ADM Capability Center (ACC) are part of the team from day one.
Operations sits within this role, including the managed-services partner relationship. You will lead its integration into the product model, so that running data products and building them are owned together rather than by a separate organization.
Key Responsibilities
Scope & Parterships
What you lead
Data engineering as a capability across data product and digital product teams, including ACC engineers: talent, standards, and delivery quality.
Operations, including the managed-services partner relationship, as part of a planned path to full integration into the product model.
Managing budgets, capacity, sourcing strategy, and vendor performance.
Lead and partner with globally distributed teams across North America, EMEA, LATAM, APAC, and the ADM Capability Center, overseeing employees and contractors, including data engineers embedded within Data Product and Digital Product teams, as well as Data Operations.
Communicating strategy, progress, risk, and value to executives, product leaders, and business partners.
Measure and report the value of the capability including productivity, cost, quality, retention, and innovation output.
Who you partner with
- Platform & Architecture, who own the data platform and architectural direction. You make sure engineers build well on them and bring what teams need back to them.
- Product teams, who own product priorities and roadmaps. You make sure they have the engineering talent and delivery quality to meet them.
- Data Governance and MDM teams, on data quality, metadata, lineage, and validation.
- Advance Analytics and AI teams to ensure data is trusted, accessible and AI ready.
Outcomes You Will Deliver
1. Data products the business trusts and uses
Production-grade, reusable data products, built and run by product teams, that are adopted across the enterprise.- Secure, scalable pipelines and data products with clear ownership, defined data contracts, and service levels for availability, freshness, quality, and resolution time.
- Production health visible by design: observability, incident and problem management, and release readiness built into every product, with Operations performance reported against agreed service levels.
2. ACC leverage
The ADM Capability Center is a fully integrated global engineering team- ACC engineers work as full members of product teams, under the same standards, expectations, and career paths.
- Depth, ownership, and scope in ACC across design, build, and operations, will be measured through productivity, quality, retention, and innovation output.
3. Engineering practices
Consistent, modern engineering practices in every data and digital product team.- Engineering standards and patterns adopted by teams, including testing, CI/CD, code review, security, privacy, and ITGC and SOX controls, as guardrails that speed delivery rather than gates that slow it.
- AI-assisted engineering and other emerging capabilities evaluated through disciplined pilots, then operationalized where they work.
4. Talent for both product models
A deep bench of data engineering talent that grows and moves across data product and digital product teams.- Hiring, development, retention, and succession for a global team, supported by a strong team culture, clear communication rhythms, and knowledge-sharing across regions and time zones.
- Capacity, sourcing, and partner mix matched to the demands of both product models, with budgets and partner performance managed to plan.
5. Data readiness
Enterprise data that is trusted, governed, and ready for analytics, operations, and AI.- Data quality, metadata, lineage, and validation built into engineering work in partnership with Data Governance, MDM, and Platform & Architecture.
- Integration across applications, files, APIs, and operational and IoT sources following shared patterns, so analytics and AI use cases move from pilot to production.
Qualifications
Required
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field (Master's preferred).
- Minimum 12 years in data engineering, data platforms, or data operations, with 5+ years leading large, global teams.
- Experience leading engineering talent embedded in product teams, and partnering effectively with platform, architecture, and product leaders.
- Experience building global teams in which capability center engineers work as full members of product teams.
- Proven delivery of production-grade data products on enterprise-scale cloud data platforms (Lakehouse/data lake, Data warehousing, ETL, batch and streaming ingestion).
- Experience setting and driving adoption of engineering standards and practices across multiple teams.
- Experience running production data operations with SLAs, observability, incident management, and ITGC/SOX-type controls, ideally within a product-aligned operating model.
- Experience managing managed-service partners alongside internal teams.
- Experience contributing to large-scale technology transformation and aligning data capabilities to enterprise strategy.
- Strong executive communication, stakeholder management, and financial acumen.
Preferred
- Hands-on exposure to AI/ML or generative and agentic AI enablement, including AI-assisted engineering.
- Background in a global, regulated, or manufacturing/supply-chain enterprise, including operational technology (OT) or IoT data.
- Familiarity with enterprise application data landscapes (e.g., ERP).
- Relevant cloud or data platform certifications.
Excited about this role but don’t think you meet every requirement listed? We encourage you to apply anyway. You may be just the right candidate for this role or another one of our openings.
ADM requires the successful completion of a background check.
REF:114765BR
ADM requires the successful completion of a background check.
REF:114765BR
Required Languages
🇬🇧 English