Data Engineer

We are looking for an experienced Data Engineer at Manager level with 8 to 10 years of experience to join an advanced analytics engagement based in Riyadh. You will work as part of a small, senior delivery team, building and optimizing the data pipelines and analytics infrastructure that power a client's advanced analytics program, with a focus on procurement and cost-optimization use cases. What You'll Do ❑ Design and build scalable data pipelines and ETL/ELT workflows on Snowflake, integrating with DataIQ and Sigma ❑ Develop and optimize Python-based data engineering workflows within the client's environment ❑ Translate procurement and cost-optimization analytics requirements into robust, production-grade data solutions ❑ Structure and model data to support advanced analytics and decision-intelligence use cases ❑ Embed data quality, governance, and lineage standards across all pipeline stages ❑ Engage directly with client stakeholders to clarify requirements and present technical approaches ❑ Own day-to-day delivery of the data workstream, including planning and quality of deliverables ❑ Collaborate with a small, senior project team — including a data architect and a junior data resource Requirements ❑ 8-10 years of data engineering experience, ideally including time at a Big 4 firm or strategy / technology consulting firm ❑ Strong hands-on experience with Snowflake; familiarity with DataIQ and Sigma Computing is a strong plus ❑ Proficient in Python and SQL for data engineering and pipeline development ❑ Experience with procurement, sourcing, or cost-optimization analytics use cases ❑ Solid understanding of data modeling, ETL/ELT design, and data quality practices ❑ Comfortable working directly within a client's technical environment under data sovereignty constraints ❑ Able to interface with client stakeholders and communicate clearly with non-technical audiences ❑ Willing and able to work on-site in Riyadh on a full time or hybrid basis (2-3 days per week) You're Our Match If You Have ❑ A track record of delivering data engineering workstreams on client-facing consulting engagements ❑ Strong command of Snowflake-based architectures and modern analytics stacks ❑ Comfort operating in fast-paced, deadline-driven project environments ❑ The ability to own your workstream with minimal oversight while coordinating with a small delivery team ❑ Professional experience in Saudi Arabia or the wider GCC ❑ Availability to start within the next month and commit to a 4-6 month contract Bonus Points If You Have Experience With ❑ DataIQ or Sigma Computing specifically ❑ Procurement or sourcing analytics and cost-optimization use cases ❑ A Big 4 firm, global systems integrator, or strategy consulting firm ❑ Arabic data sets ❑ Working under data residency / sovereignty constraints in client environments Show more Show less

8-10 years of data engineering experience, ideally including time at a Big 4 firm or strategy / technology consulting firm. Strong hands-on experience with Snowflake; familiarity with DataIQ and Sigma Computing is a strong plus. Proficient in Python and SQL for data engineering and pipeline development. Experience with procurement, sourcing, or cost-optimization analytics use cases. Solid understanding of data modeling, ETL/ELT design, and data quality practices. Comfortable working directly within a client's technical environment under data sovereignty constraints. Able to interface with client stakeholders and communicate clearly with non-technical audiences. Willing and able to work on-site in Riyadh on a full time or hybrid basis (2-3 days per week).

Design and build scalable data pipelines and ETL/ELT workflows on Snowflake, integrating with DataIQ and Sigma. Develop and optimize Python-based data engineering workflows within the client's environment. Translate procurement and cost-optimization analytics requirements into robust, production-grade data solutions. Structure and model data to support advanced analytics and decision-intelligence use cases. Embed data quality, governance, and lineage standards across all pipeline stages. Engage directly with client stakeholders to clarify requirements and present technical approaches. Own day-to-day delivery of the data workstream, including planning and quality of deliverables. Collaborate with a small, senior project team — including a data architect and a junior data resource.