Digital Zone

Regional digital platform for daily finances

Senior Data Engineer

Data EngineeringPosted on Nov 11

Full-timeBaghdad, Baghdad Governorate, IraqNo salary listed

About the Job

Requirements

Have 5 to 8 years of experience building production software or data systems, including 3 or more years in data engineering owning business-critical pipelines.
Have expert-level SQL skills and strong Python skills, along with dimensional modeling skills and the judgment to choose an appropriate model for each use case.
Have hands-on experience with a cloud warehouse, modern orchestration and transformation tools such as dbt, Airflow or Dagster, and working knowledge of Postgres and AWS.
Have hands-on experience deploying and operating machine learning models in production with data scientists, including feature pipelines, batch or real-time serving, model versioning, and monitoring; examples include MLflow and SageMaker.
Have experience with both batch and streaming ingestion, including change data capture, late and duplicate events, and schema evolution.
Reconcile data against source systems and ensure pipeline results are correct, even when a pipeline runs successfully.
Communicate effectively with technical and non-technical audiences and work with stakeholders to agree on metric definitions.

Responsibilities

Design, build and own end-to-end production pipelines for batch and streaming data, ingesting from Digital Zone services such as Postgres/Aurora and event streams, as well as third-party providers, with idempotent loads and safely rerunnable backfills.
Model data for the warehouse and semantic layer by turning agreed metric definitions into tested, documented models that produce consistent results.
Implement data quality through tests, freshness service-level agreements, lineage and alerting that detect upstream failures; participate in the team's on-call rotation.
Partner with data science to move models from notebooks to production through feature pipelines, training datasets, model deployment and serving, and monitoring for drift and data quality after launch.
Work with product and engineering teams on event tracking and data contracts so instrumentation is built into services and schema changes do not silently break pipelines.
Implement appropriate access control, masking and retention for personally identifiable information, including passport and telecom identifiers, across markets with differing regulatory expectations.
Balance warehouse compute, storage and tooling costs against value, and make tradeoffs visible.
Use AI-assisted development judiciously by reviewing generated SQL and pipeline code and validating it against real data.
Mentor teammates and document the platform through runbooks, architecture decision records and documented models so critical pipelines can be supported by others.

Desired Qualifications

Have analytics experience with e-commerce, payments, marketplace or fintech products, including multi-currency and multi-market reporting.
Have experience with a feature store or MLOps platform, or machine learning use cases such as fraud, risk or personalization.
Have experience on an early-stage data team or consolidating fragmented reporting across business units.
Be familiar with TypeScript or Go to work comfortably in the services that produce Digital Zone's data.

Senior Data Engineer

Digital Zone · Baghdad, Iraq (Hybrid) · Full-time · Posted 2026-11-11

Workplace: hybrid

Department: Technology

Description

As a Senior Data Engineer, you will build the pipelines and models the rest of DZ will 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 and its own version of the numbers. As one of the first engineers in the new data team, you will own core parts of the data platform end to end, from ingestion off operational systems and third parties through to the modeled tables that finance, commercial and product use to make decisions, and the path that takes data science models from notebook to production. This role is about making data correct, fresh and trusted by default, so the answer stops depending on who pulled it.

What you'll do

Design, build and own production pipelines end to end, batch and streaming: ingestion from DZ's services (Postgres/Aurora, event streams) and third-party providers, with idempotent loads and backfills that are safe to rerun.
Model data for the warehouse and the semantic layer, turning agreed metric definitions into tested, documented models that give the same answer every time.
Treat data quality as part of the job, not a cleanup: tests, freshness SLAs, lineage and alerting that catch upstream breaks before a stakeholder does. You'll be an active participant in the team's on-call.
Partner with data science to take models from notebook to production: feature pipelines, training datasets, model deployment and serving, and monitoring for drift and data quality once they are live.
Work with product and engineering teams on event tracking and data contracts, so instrumentation is designed into services rather than bolted on, and schema changes stop silently breaking pipelines.
Handle sensitive data correctly by design: access control, masking and retention for PII (passport and telecom identifiers) across markets with different regulatory expectations.
Weigh cost against value in warehouse compute, storage and tooling, and make the tradeoffs visible.
Use AI-assisted development with judgment: review generated SQL and pipeline code like a peer PR, and check it against real data, not only whether it runs.
Mentor teammates and keep the platform legible through runbooks, ADRs and documented models, so you are not the only person who can support a critical pipeline.

Requirements

What you'll bring

5 to 8 years building production software or data systems, with 3+ years in data engineering owning pipelines the business depended on.
Expert SQL and strong Python, solid dimensional modelling, and the judgment to choose the right model for the use case.
Hands-on experience with a cloud warehouse and modern orchestration and transformation tooling (for example dbt, Airflow or Dagster), plus working knowledge of Postgres and AWS.
Hands-on experience deploying and operating ML models in production alongside data scientists: feature pipelines, batch or real-time serving, model versioning, and monitoring (for example with MLflow, SageMaker or similar).
Experience with both batch and streaming ingestion, including change data capture, late and duplicate events, and schema evolution.
A correctness mindset: you reconcile numbers against the source, and you know a pipeline that runs green can still be wrong.
Communication that lands with technical and non-technical audiences, including the patience to get stakeholders to agree on what a metric means.

Nice to have

Analytics experience on e-commerce, payments, marketplace or fintech products, including multi-currency and multi-market reporting.
Experience with a feature store or MLOps platform, or with ML use cases such as fraud, risk or personalisation.
Experience on an early-stage data team, or consolidating fragmented reporting across business units.
Familiarity with TypeScript or Go, to work comfortably in the services that produce DZ's data.

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

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About the Company

Digital Zone

Regional digital platform for daily finances

Digital Zone is a regional technology company that builds an interconnected ecosystem of apps—TicketZone, Rahal, and DigitalZone—to serve daily digital needs for people and families in the Middle East. It operates by integrating its apps into one platform that supports ticketing, payments/finances, and other digital life services, enabling users to access and manage services and spend in a single place with security and intelligence. Unlike many competitors that offer single-purpose apps, Digital Zone focuses on embedding its services into everyday life, building a trusted, large user base and moving toward a platform model. The company’s goal, captured in Vision 2028, is to create a social financial platform that organizes digital life spend in one secure, intelligent space.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: Baghdad, Iraq
Founded: 2020

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