Data Engineer
Senior Data Engineer
Location: Abu Dhabi, UAE - Remote Global
Type: Contract
Role Summary
We are seeking a Senior Data Engineer to architect and build the foundational data infrastructure for
a large-scale AI transformation programme. You will move beyond standard ETL tasks to design and
deploy enterprise-grade Data Lakehouses that serve as the "Single Source of Truth" for AI agents and
advanced analytics platforms.
You will lead the technical execution of data and platform foundation initiatives. Your mandate is to
map rigid enterprise systems (e.g., SAP S/4HANA, Ariba, etc.) and collaborate with teams to
understand complex unstructured data (technical drawings, regulatory text) while building high
performance pipelines and systems that power Intelligent Supply Chain forecasting and generative AI
tools.
You will operate within a structured "Sprint Zero" environment, ensuring data lineage, governance,
and security meet strict enterprise standards.
Key Responsibilities
1. Data Lakehouse Architecture (Supply Chain)
* ERP Integration: Architect and deploy ingestion pipelines to extract high-volume
transactional data from SAP S/4HANA, Ariba, and PLM systems, ensuring near real-time
availability for forecasting models.
* External Feed Integration: Build connectors for external market intelligence feeds (e.g., S&P
Global, Orbis, EcoVadis) to enrich internal procurement data with macroeconomic and
geopolitical signals.
* Unified Data Model: Design and implement a standardized procurement data model and
taxonomy across multiple entities, harmonizing fragmented datasets into a cohesive layer for
analytics.
2. Unstructured Data Pipelines
* Complex Ingestion: Engineer pipelines to ingest and process unstructured technical data,
including PDF tender documents, CAD metadata, and historical CONOPS, transforming them
into vector-ready formats for RAG (Retrieval-Augmented Generation) applications.
* Vector Database Management: Manage and optimize Vector Databases (e.g., Weaviate) to
store embeddings of archival proposals and engineering snippets, ensuring high-speed
retrieval for AI drafting assistants.
* Digital Thread Implementation: Establish data lineage and traceability protocols that link
requirements to physical components, supporting Model-Based Systems Engineering (MBSE)
Digital Thread initiatives.
3. Governance & Security
* Enterprise-Grade Security: Implement Role-Based Access Control (RBAC), audit logging,
and data redaction policies to ensure compliance with export controls and strict on-premise
security requirements.
* Quality Control: Deploy automated data quality frameworks to validate BOM (Bill of
Materials) completeness and cost data accuracy before it reaches AI models.
* Infrastructure Optimization: Optimize pipelines for on-premise GPU clusters and air-gapped
environments, ensuring efficiency within existing infrastructure limits.
Technical Requirements
* Core Stack: Expert proficiency in Python, SQL, and modern data engineering frameworks
(Apache Spark, Kafka, Airflow).
* Enterprise ERP: Strong experience extracting data from complex ERP environments,
specifically SAP S/4HANA and SAP Ariba. Familiarity with SAP BTP is a plus.
* Database Technologies: Deep understanding of Data Lakehouse architectures
(Databricks/Delta Lake), Relational Databases (PostgreSQL), and Vector Databases
(Weaviate/Milvus).
* Data Pipeline Development: Experience building pipelines for RAG solutions, conversational
agents, and classical ML models using tools such as dbt, Dagster, or Prefect.
* DevOps/DataOps: Proficiency with containerization (Docker, Kubernetes) and CI/CD
pipelines for deploying data workflows in secure environments.
Professional Qualifications
* Experience: 5+ years of experience in Data Engineering, with at least 2 years focused on
building pipelines for Machine Learning or Generative AI applications in an enterprise setting.
* Domain Knowledge: Experience in Supply Chain, Manufacturing, or Defence sectors is
highly desirable. Ability to understand Bill of Materials (BOM) structures and procurement
lifecycles.
* Problem Solving: Ability to navigate the "Governance Collision" between agile data work and
rigid systems engineering requirements, ensuring data deliverables meet formal Stage Gate
reviews.
* Collaboration: Proven ability to work alongside Data Scientists and Backend Engineers to
define data schemas that support predictive modelling and AI agents.
Why This Role?
You will be the architect of the data foundation behind advanced AI capabilities. Your work will directly
enable AI agents to support procurement workflows, forecasting, analytics, and engineering decision
making. If you are ready to build the robust infrastructure that turns raw data into strategic advantage,
this role is for you.
GCS is acting as an Employment Business in relation to this vacancy.
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