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

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.

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.

Data Solution Architect, Supply Chain – Part-Time Consultant

Key skills