We are growing a capability within the Supply Chain BU to enable AI-driven transformation for enterprise clients (3PL, retail, manufacturing, logistics platforms), and looking for a Data Solution Architect (Supply Chain, Part-Time Consultant). The focus is on helping organisations transition from fragmented, siloed data ecosystems to scalable, governed, and AI-ready data platforms.
This role will operate across:
- Client engagements (delivery) – designing and implementing modern data platforms and pipelines
- Pre-sales activities – shaping data architecture strategies, conducting data maturity assessments, and defining AI readiness roadmaps
- Enterprise data advisory – defining and driving enterprise data strategy, ensuring alignment between business objectives, data architecture, and AI adoption
The Data SA will play a critical role in:
- Defining enterprise-wide data strategy, target-state architecture, and a roadmap
- Establishing governed, scalable data foundations required for AI/ML adoption
- Designing data platform architectures that enable data-driven decision-making across supply chain operations
Innovecs is a global digital transformation tech company with a presence in the US, the UK, the EU, Israel, Australia, and Ukraine. Specializing in software solutions, the Innovecs team has experience in Supply Chain, Healthtech, Software & Hightech, and Gaming.
For the fifth year in a row, Innovecs is included in the Inc. 5000 and recognized in IAOP’s ranking of the best global outsourcing service providers. Innovecs is featured in the Global Top 100 Inspiring Workplaces Ranking and won gold at the Employer Brand Management Awards.
If you feel like you’re the perfect match for this role, drop us your CV!
There are no limitations, no barriers when the right people are on your way — apply for the vacancy and succeed with us!
Innovecs is an equal opportunity employer. All hiring decisions are based on professional qualifications, skills, and experience. We are committed to a transparent, merit-based recruitment process that prevents discrimination and ensures equal opportunities for all candidates. Reasonable accommodations are available upon request throughout the recruitment process to support accessibility and inclusion.
- 8+ years of experience in data architecture, and hands on data engineering.
- Experience in Supply Chain industry (WH operations, WMS, TMS, EDI, YMS, etc.)
Strong hands-on experience building and optimising:
- Batch and streaming data pipelines
- ETL/ELT processes
Scalable and high-performance data solutions.
Optimise data platforms for performance and cost efficiency, balance scalability, reliability, and cost.
Deep understanding of:
- Medallion architecture (Bronze / Silver / Gold)
- Data modeling approaches (dimensional, Data Vault, lakehouse modeling).
Proven experience defining and implementing:
- Enterprise data governance frameworks (data ownership, stewardship, lineage, quality standards).
- Data management operating models aligned with business domains.
Experience establishing:
Data standards, naming conventions, and metadata management practices.
Clear communication, proactive attitude, strong sense of ownership & accountability, experience of presenting the complex concepts in a tailored to the audience manner.
Experience in client-facing roles, including: running workshops and discovery sessions, presenting architecture and strategy to senior stakeholders.
- Define and lead enterprise data strategy, aligning business goals, data architecture, and AI/ML adoption
- Design and implement modern cloud data platforms (lakehouse, data warehouse, streaming architectures)
- Establish and enforce data architecture standards
- Own and define enterprise data governance frameworks, including data ownership, stewardship, lineage, metadata, and data quality standards
- Establish data management operating models and governance processes across business and engineering teams
- Design and build scalable, reliable, and high-performance data pipelines
- Optimize data platforms for performance, scalability, and cost efficiency
- Ensure data quality, consistency, and accessibility across all data layers
- Enable AI-ready data platforms, ensuring governed, traceable, and high-quality datasets for analytics and ML
- Conduct data maturity assessments and define transformation roadmaps
- Lead client workshops, architecture discussions, and pre-sales engagements
- Create and present solution architectures, proposals, and technical strategies
- Act as a trusted advisor to C-level stakeholders and engineering teams
- Develop reference architectures, best practices, and reusable assets
- Mentor engineers and contribute to building a high-performing data engineering and architecture capability
