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. Please note we can only consider candidates based in Europe - remote or hybrid set-up depending on location. ResponsibilitiesData 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.

Requirements5+ 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. Our OfferCompetitive salary synonymous with skills and experiencePerformance and bonus structure dependent on achievement of set targets and personal performanceConsultancy contract within EU on a full time basis with 25 days PTOor employment contract if you are based in London, Sofia or Malta