Data Engineering Manager

You will build and lead the team that turns DZ’s data into something the business can actually run on. DZ operates across several verticals and markets: digital goods, ticketing, travel, and trading in Iraq, the UAE, and KSA. Each has grown its own reporting, metric definitions, and version of the numbers, so basic questions take days and the answers do not always agree. You will hire the team, own the data platform end to end—from ingestion through the warehouse and modelling to the analytics layer—and make trusted data a capability the rest of the organisation can rely on rather than a queue it waits behind.

What you’ll do

• Build and lead the data team: hire, mentor, and grow data and analytics engineers, and set the bar for a function that every other team depends on daily.
• Own the technical strategy and architecture for the data platform: ingestion from operational systems and third parties, the warehouse and modelling layer, orchestration, and the semantic layer that keeps metrics consistent across verticals.
• Establish a single source of truth for core business metrics, with definitions agreed on with commercial, finance, and product teams, and pipelines that make the numbers reproducible and trusted.
• Deliver self-serve analytics so most questions are answered without a ticket, and the team’s time goes to platform work rather than ad hoc pulls.
• Treat data as a product and own its reliability: freshness SLAs, lineage, testing, and alerting that fires when something breaks upstream rather than when a stakeholder notices.
• Partner with security and legal teams on governance, access control, retention, and the handling of PII, including passport and telecom identifiers, across markets with different regulatory expectations.
• Build the foundation the next stage depends on: event-tracking standards, experimentation, and the data that data science, personalisation, fraud, and risk will need.
• Partner with product and engineering teams so instrumentation and data contracts are designed into services rather than bolted on afterwards.

Requirements

What you’ll bring

• Eight or more years in software or data engineering, with three or more years leading engineering teams, including hiring and growing engineers.
• Direct experience building and operating a production data platform: batch and streaming ingestion, warehouse modelling, orchestration, and the operational discipline to keep it reliable at scale.
• Strong hands-on technical judgment to lead design reviews and make build-versus-buy and cost trade-offs on warehouse and tooling spend. Deep SQL and dimensional modelling skills, and comfort working in a Python, TypeScript, Go, Postgres, and AWS environment.
• A track record of getting an organisation to agree on metric definitions, not just shipping pipelines. Much of this role involves aligning people who currently disagree about what a number means.
• Governance instincts: treating access, PII, and retention as design inputs rather than as an audit exercise.
• The judgment to sequence a platform build so the business sees value early, without laying a foundation that has to be torn up in a year.

Nice to have

• Experience standing up a data function from zero or consolidating fragmented reporting across business units.
• Analytics experience with e-commerce, marketplace, payments, or fintech products.
• Experience supporting data science and machine learning in production, including feature pipelines, model serving, or MLOps.
• MENA or emerging-market experience, including multi-currency and multi-market reporting.

Benefits

• Immediate, large-scale impact on a high-growth business.
• Top-of-the-market compensation packages.
• Work alongside top regional talent, with team members from Talabat, Careem, Etisalat, and more.