The Role:

Ziina is looking for a Senior Data Platform Engineer to join our team. This role is an exciting opportunity to build the foundations of our data platform from the ground up — the pipelines, warehouse, and tooling that will power decision-making, analytics, and future ML/AI capabilities across the company. We're at a major inflection point in our growth, and we're looking for the right person to shape how data is ingested, modeled, and consumed at Ziina as we scale.

As part of a small, agile team, our ideal candidate is a creative problem-solver with the vision to build from the ground up and the skill to own systems end-to-end. You'll thrive in our fast-paced environment by making sound tradeoffs and focusing on high-impact solutions. We're looking for someone who is as ambitious as we are to deliver high-quality products to our users. In short, we want owners who are ready to build big things with us.

As a Senior Data Platform Engineer at Ziina you will:

• Build and maintain scalable data pipelines and processing systems that ingest data from transactional databases, object storage, and external APIs
• Design and evolve our data warehouse architecture and data models to support analytics, reporting, and ML/AI use cases
• Improve the reliability, observability, and performance of our data systems
• Implement data quality checks and monitoring to ensure trusted, accurate data across the company
• Enable self-service data access and analytics so product, engineering, and business teams can make data-driven decisions independently
• Support the foundational capabilities that will power our ML and AI use cases as they grow

To succeed in this role, you likely:

• Bring 5+ years of experience in Data Engineering, Data Platform, or Analytics Engineering
• Have strong expertise building and maintaining data pipelines with orchestration tools like Dagster, Airflow, or Prefect, and writing ETL/ELT workflows in Python
• Are proficient with modern data warehouses (Snowflake, BigQuery, or Redshift) and transformation frameworks like dbt
• Have hands-on experience ingesting data from a mix of sources — PostgreSQL, S3, external APIs — supporting both transactional and event-driven use cases
• Are familiar with data quality, observability, and monitoring practices for production data systems
• Use the latest AI tools and technologies to boost your productivity
• Are based in, or open to relocating to, the UAE

What would amaze us

• Proven experience building data platforms at fintech or other high-scale, high-reliability companies
• A track record of designing data warehouse architectures and models that scaled cleanly as the company grew
• History of building self-service analytics tooling that meaningfully expanded who in the company could work with data
• Experience enabling ML/AI workloads on top of a data platform — feature stores, ML pipelines, or serving infrastructure
• Active engagement in the data community through open source contributions, conference speaking, or technical writing

Our tech stack:

The data platform is a core investment area at Ziina. Our current stack is:

• Snowflake as our data warehouse, with dbt for data transformation and modeling
• Dagster for orchestrating data pipelines, with Python for building ETL/ELT workflows
• Data ingestion from PostgreSQL, S3, and external APIs, supporting both transactional and event-driven use cases
• Metabase for analytics and internal reporting

The broader Ziina engineering stack that the data platform integrates with:

• Typescript, Node.js and Nest.js for our main application's backend
• GraphQL Federation for our client-facing APIs and Kafka for our inter-service communication
• PostgresSQL for consistent and durable storage, Redis for quick fetching, Elasticsearch for quick searching
• AWS for hosting our cloud infrastructure and Kubernetes for orchestrating our workloads
• Terraform for IaC, GitHub Actions for CI/CD