Data Platform Engineer/Architect (Contractor)

About the role

Devtech is seeking a senior engineer to build a data warehouse from the ground up and evolve it into an AI‑enabled platform. The role covers the full lifecycle—from foundational ingestion, modelling and reporting to preparing data for generative AI use cases.

Key responsibilities

• Design and implement a scalable data warehouse, including robust data modelling that can accommodate new source systems.
• Build and orchestrate ingestion pipelines with quality gates, monitoring, and incremental processing.
• Own data hygiene activities such as cleansing, deduplication, validation and reconciliation across sources.
• Define a semantic layer with shared metric and entity definitions for enterprise‑wide use.
• Deliver the first reporting iteration using Power BI dashboards, drill‑down reports and operational KPIs.
• Prepare the platform for AI by establishing governance, access control and data shaping for model consumption.
• Implement RAG and agent enablement features, including embeddings, vector search and document retrieval design.
• Create an AI roadmap that sequences analytics, predictive models and internal AI assistants.

Required profile

• Proven end‑to‑end experience designing and delivering data warehouses across multiple source systems.
• Strong expertise in ingestion and orchestration engineering (batch and incremental pipelines, automated quality gates, monitoring).
• Demonstrated ability to improve data quality and hygiene, turning messy source data into trustworthy assets.
• Experience with semantic layer and dimensional modelling.
• Hands‑on BI delivery experience, preferably with Power BI.
• Solid understanding of data governance fundamentals (lineage, access control, PII handling).
• Practical familiarity with AI data enablement concepts such as RAG, embeddings and vector databases.

Required skills

• Data warehouse design and implementation
• ETL/ELT pipeline development
• Power BI reporting
• Data governance (lineage, access control, PII)
• AI data enablement (RAG, embeddings, vector databases)