Senior Data Platform Engineer

About 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

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