Senior Data Engineer

We are looking for a Senior Data Engineer to join our growing Data team and play a key role in shaping and scaling our data infrastructure. This position is ideal for a highly skilled and motivated engineer who thrives in a fast-paced iGaming environment and is passionate about building robust data systems that power business-critical decisions.

Reporting directly to the Head of Data, you will take ownership of a wide range of engineering responsibilities—from building and maintaining new data integrations (batch and streaming), to automating pipelines and designing scalable data models. This role is pivotal in offloading the day-to-day engineering tasks and driving long-term data excellence across the company.

Tasks

• Data Architecture: Design and implement robust, scalable data architecture to support the collection, storage, and processing of large volumes of iGaming and customer data.
• ETL Development: Build and maintain efficient ETL and ELT processes to ensure seamless data ingestion from multiple sources into our data lake, DWH, and final consumers.
• Data Modeling: Create and maintain well-structured data models that ensure accuracy, integrity, and optimal performance for analytical use cases following Kimball best practices.
• Data Integration: Collaborate with cross-functional teams to integrate data across systems, with several types of integration as API, Kafka, DB extractions, Webscrapping, Email, etc.
• Streaming & Real-Time Processing: Develop and manage real-time data pipelines using streaming technologies (e.g., Kafka) to support time-sensitive use cases.
• Data Quality & Governance: Enforce data governance policies and best practices, ensuring high standards for data quality, security, and regulatory compliance.
• Performance Optimization: Continuously monitor, troubleshoot, and optimize data pipelines, queries, and infrastructure for speed, efficiency, and reliability.
• Pipeline Orchestration: Support and expand production-grade orchestration workflows using Apache Airflow.
• Observability & Monitoring: Set up and maintain monitoring, alerting, and observability for data pipelines and systems using tools like Elementary, Datadog, Prometheus, or Grafana.
• CI/CD and Automation: Develop and maintain CI/CD pipelines for data projects using Bitbucket Pipelines or GitHub Actions, ensuring streamlined deployment and testing processes.
• Version Control & Collaboration: Follow best practices in Git-based version control and work collaboratively in a modern DevOps environment.

Requirements

• 5+ years of experience with Python, preferably including 2+ years working with Airflow.
• 5+ years of experience with SQL in big data environments, preferably including 2+ years with dbt.
• 4+ years in cloud environments, preferably with 2+ years each in Snowflake and AWS.
• 2+ years of experience with data streaming platforms, preferably on Kafka.
• 2+ years of hands-on experience with containerization (Docker, Kubernetes).
• 3+ years managing CI/CD pipelines, ideally using Bitbucket Pipelines or GitHub Actions.
• Deep understanding of data governance, data quality, and data lineage principles.
• Proficient in using monitoring and alerting tools such as Datadog, Prometheus, or Grafana.
• Solid experience with version control tools (Git) and IaaS (e.g., Terraform).
• Strong communication and problem-solving skills, with a proactive and self-driven attitude.

Benefits

• Competitive salary synonymous with skills and experience
• Performance and bonus structure dependent on achievement of set targets and personal performance
• Consultancy contract within EU on a full time basis with 25 days PTO
• or employment contract if you are based in London, Sofia or Malta