Designing solutions for data ingestion, storage, processing, transformation, enrichment, and presentation for analytical purposes.
Eliciting requirements and customizing analytical architectures to meet customer needs.
Designing and building data pipelines and strategies.
Coaching clients and internal teams on the latest architectures and methodologies (DataOps, MLOps, etc.).

15+ years of experience in data engineering.
Bachelor’s degree in Computer Science, Computer Engineering or other quantitative field. Post Graduate degrees preferable.
The ability to interact with stakeholders at multiple levels within a given organization, understand current analytical challenges and gathering requirements.
A deep understanding of the evolution of analytical architectures from reporting databases to data warehouses, data lakes, data lakehouses, data fabrics, data meshes and beyond. A data architect should also be able to technically justify how a proposed architecture would suffice a potential client’s analytical needs.
Extensive experience with Microsoft on-prem Data Platform or equivalent (SSIS, SSAS & SSRS).
Experience with optimizing query performance and setting up high availability configurations.
Experience with multiple data cloud vendor such as Microsoft Azure data services (e.g. MS Fabric, ADF, …) or AWS (S3, Lake Formation, Glue, Redshift, Kinesis,..)
Experience with Large Processing store (Databricks or Snowflake) or equivalent
Strong Data warehouse Architecture and Dimensional modeling knowledge
Experience with Vibe Coding (e.g. Cursor/Codex/Claude Code)
Experience with building Agentic Frameworks and LLM orchestration (e.g. LangGraph/AutoGen/CrewAI/Llamaindex/n8n)
Experience with Agent Protocol (e.g. MCP)
Familiarity with DataOps.

Data Architect

Key skills