Data and AI Architect

Refresco•Egypt Lake-Leto, FL

18h•Hybrid

About The Position

The Data Architect is the senior technical lead for the enterprise data and AI platform at Refresco. This role designs, builds, and governs a modern open data ecosystem anchored on SAP Business Data Cloud (BDC) while architecting AI-powered solutions using SAP BTP, SAP AI Core, HANA Cloud, and GenAI/LLM platforms. The Data Architect partners closely with the IT leadership and works across Business Applications, functional teams, and business stakeholders to translate complex data and AI needs into scalable, governed, and business-aligned platform capabilities. The ideal candidate combines deep SAP expertise with hands-on data engineering fluency and an active AI practitioner mindset.

Requirements

Bachelor’s degree in computer science, Information Systems, Data Science, Engineering, or related field required; Master's degree preferred.
15+ + years of experience in data architecture, data engineering, or BI/analytics roles in enterprise environments.
Minimum 3+ years of deep, hands-on SAP experience — BDC, Datasphere, BW/4HANA, and S/4HANA analytics.
Demonstrated experience delivering GenAI or agentic AI solutions in enterprise environments, from prototyping to production.
Demonstrated experience building production data pipelines using Python and SQL alongside SAP-native tooling.
SAP Platform: Hands-on expertise with SAP BDC, Datasphere, BTP (AI Core, Integration Suite, Extension Suite), HANA Cloud (including vector processing and Knowledge Graphs), BW/4HANA, SAC, and S/4HANA CDS/AMDP.
AI & GenAI: Proficiency with Lang Chain, LangGraph, RAG/Graph RAG, vector databases, LLM platforms (Azure OpenAI, AWS Bedrock, SAP GenAI Hub), A2A/MCP frameworks, prompt engineering, and SAP Business AI / Joule.
Data Engineering: Strong command of Python (Pandas, PySpark, SQLAlchemy), SQL, dbt, Apache Airflow/Spark, Git/CI-CD, and open data formats (Parquet, Delta Lake, Iceberg).
Architecture & Governance: End-to-end data architecture design, data governance frameworks, metadata and lineage tooling, RBAC, AI security, and hyperscaler integration patterns (Azure, AWS, GCP).
Strategic and analytical thinker with the ability to translate complex data and AI needs to platform decisions that deliver measurable business value.
Strong communicator able to articulate technical concepts clearly to both engineering teams and non-technical business stakeholders.
Highly process-oriented with the ability to enforce documentation standards, architecture review practices, and repeatable delivery disciplines.
Proactive and curious; stays ahead of SAP BDC/BTP roadmap updates, LLM platform advances, and open-source data engineering innovation.

Nice To Haves

Experience in manufacturing, CPG, or similarly complex operational environments is a strong differentiator
SAP BDC, BTP AI Core, or Datasphere certifications are advantageous; cloud AI certifications (Azure AI, AWS ML) and TOGAF are a plus.

Responsibilities

Own and evolve the enterprise data architecture centered on SAP BDC, Datasphere, and BTP — including Medallion architecture, Data Products, Delta Lake, and zero-copy sharing — ensuring alignment with Business Applications strategy and clean-core principles.
Design cross-platform integrations across SAP S/4HANA, BW/4HANA, non-SAP systems (IoT, SaaS, OT data), and hyperscalers (Azure, AWS, GCP) to enable a unified, governed data fabric.
Build and maintain enterprise-grade data pipelines using Python, SQL, dbt, Airflow, and Spark alongside SAP-native tools (ODP/CDS extraction, Datasphere Data Integration), with CI/CD practices and pipeline observability standards.
Optimize SAP HANA Cloud for real-time analytics and AI workloads — including advanced SQLScript, vector embeddings, and Knowledge Graphs — to support both operational and analytical consumption patterns.
Architect and deploy GenAI and ML solutions using SAP AI Core, SAP AI Launchpad, and LLM platforms (Azure OpenAI, AWS Bedrock, SAP GenAI Hub), integrating them seamlessly into SAP business processes.
Design agentic AI workflows that automate decision-making by combining LLMs, structured SAP data, and enterprise APIs — using frameworks including LangChain, LangGraph, A2A, and MCP.
Build RAG and Graph RAG applications using HANA Cloud Vector Engine and SAP Knowledge Graphs to ground AI outputs in trusted enterprise data.
Identify and prioritize high-value AI/ML use cases across business processes and lead delivery from prototype to production in collaboration with business and IT teams.
Establish and enforce data governance frameworks covering data ownership, lineage, metadata management, data quality, and access controls using catalog tooling (SAP Metadata Explorer, Collibra, Alation, or equivalent).
Define and operationalize Responsible AI practices — including model risk, explainability, bias detection, and ethical AI compliance — aligned with enterprise policy and regulatory requirements.
Enable governed self-service analytics across SAP BDC, SAC, Datasphere, and Power BI, including semantic modeling, row-level security, and role-based access.
Lead high-complexity data and AI projects end-to-end, including stakeholder alignment, scope management, and status reporting to leadership.
Mentor junior data team members on architecture patterns, engineering standards, and AI best practices; maintain technical decision logs and platform documentation.

Benefits

Medical/Dental/Vision Insurance
Health Savings Accounts and Flexible Spending Accounts
Life and AD&D Insurance, critical illness, hospital indemnity, and accident insurance
Short-term disability and long-term disability
Pet Insurance
Legal Benefits
401(k) Savings Plan with Company Match
12 Paid Holidays
Vacation Days and Paid Sick Time Off Days
Well-being Benefit
Discount and Total Reward Programs