
Data Engineer
At a Glance
- Category
- 💻 Technology
- Level
- Mid-Level
- Type
- Contract
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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
❑ 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
Requirements
- •8–10 years of data engineering experience
- •Experience at a Big 4 firm or strategy / technology consulting firm preferred
- •Strong hands-on experience with Snowflake
- •Proficient in Python and SQL for data engineering
- •Experience with procurement, sourcing, or cost-optimization analytics
- •Solid understanding of data modeling, ETL/ELT design, and data quality
- •Professional experience in Saudi Arabia or the wider GCC
- •Ability to work on-site in Riyadh (full-time or hybrid)
Nice to Have
- •Familiarity with DataIQ and Sigma Computing
- •Experience with Arabic data sets
- •Experience working under data residency / sovereignty constraints
- •Experience with global systems integrators
Responsibilities
- •Design and build scalable data pipelines and ETL/ELT workflows on Snowflake
- •Develop and optimize Python-based data engineering workflows
- •Translate procurement and cost-optimization analytics requirements into production-grade solutions
- •Structure and model data to support advanced analytics and decision-intelligence
- •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
- •Collaborate with a small, senior project team including a data architect and junior resource
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