Ensure data products also power ML workflows: trusted training datasets, feature-ready outputs, and consistent definitions for decision-making.
Enable AI automation by delivering reliable, low-latency, governed data products that can be used safely in automated workflows.
Partner closely with product, engineering, and security stakeholders to align data products to roadmap priorities and customer outcomes.
Raise the technical bar through architecture reviews, standards, and mentoring—while staying hands-on in key systems.
Required
Significant experience building and operating production data platforms at scale, including on-call and operational ownership.
Strong SQL skills and strong Python skills, used to build pipelines, services, and automation.
Hands-on experience running cloud systems on AWS and Google Cloud (IaaS level: compute, storage, networking, IAM).
Practical experience with both operational databases (RDS-style) and analytics stores (columnar/OLAP), including performance tuning.
Strong data modeling ability, including schema evolution, conformed dimensions, and “one source of truth” metric definitions.
Track record of delivering data products that other teams or customers depend on, with clear contracts and reliability expectations.
Ability to make sound engineering tradeoffs across latency, accuracy, cost, and security without creating brittle complexity.
Experience with lakehouse patterns and open table formats (or similar), including governance and table maintenance.
Experience with orchestration and streaming systems used in production (batch + real-time), and managing backfills safely.
Familiarity with ML data needs (training/serving splits, feature-ready datasets, evaluation datasets) and AI-adjacent workflows.
Preferred
Experience building self-service data platforms (catalog, discoverability, access controls) used by multiple teams.
Experience in regulated or security-sensitive environments, including retention, auditing, and data access controls.
Work model, location & travel
Location: Belfast, UK
Reports to: VP of Data Engineering
Work model: Hybrid (details TBD)
Collaboration hours: Flexible; overlap with UK and US time zones
Travel: Minimal
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Black Duck is an equal opportunity employer. We consider all applicants for employment without regard to race, color, national origin, religion, sex, gender identity or expression, age, disability, sexual orientation, veteran or military service status, or any other characteristic protected by applicable law. Black Duck complies with all applicable laws prohibiting employment discrimination in every jurisdiction where it operates and provides reasonable accommodations to individuals with disabilities in accordance with applicable law.