- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
- 2+ years of professional software engineering experience.
- 1+ years of experience with stream or batch processing, in Flink or Spark.
- 1+ years of experience working with data warehouses, writing complex SQL queries, and optimizing workloads for speed and efficiency.
- Deep understanding of distributed systems, modern data and event-driven architectures, stream-processing concepts and technologies, such as Kafka, Pulsar, and RabbitMQ.
- Familiarity with Agile methodology, containerization, continuous integration/deployment, cloud environment, and system monitoring.
- Ability to write clean, efficient, maintainable, and well-tested code; at least one of Python/Java/Golang skills are required.
- Analytical thinking, troubleshooting skills, ability to work autonomously, and attention to detail.
- Good communication skills in verbal and written English.
Nice to have
- Experience with Bi-temporal Data Modelling, Data Lakes, Workflow Management Tools (Prefect, Argo), BI Tools (Looker, or similar), DBT, or other modern Big Data tech.
- Knowledge of Terraform (or other IaC) and Kubernetes.
- Experience setting up monitoring and alerting in Grafana (or similar tools).
- Experience working with Data Scientists and on MLOps-related problems.
BlueLabs is a dynamic and fast-growing startup in the sports betting industry. We are committed to delivering innovative and cutting-edge solutions to our customers, providing an unparalleled betting experience. As we continue to expand to new markets and evolve our product, we are looking for a highly skilled and passionate Data Engineer to join our team.
Our Technology Stack
Our Data ecosystem includes hundreds of data ingestion, transformation, or other processing steps, several integrations with 3rd parties, data consistency checks, and hundreds of user-facing dashboards and visualizations. We use Apache Pulsar for real-time data transport, Apache Flink and Benthos for stream processing, Spark for batch processing, SingleStore for data warehouse, DBT for ELT, GCS as an object store, Postgres (Citus) for online data stores, and Looker for BI & analytics.
Our release process is fully automated, enabling our small engineering team to perform several deployments per day without breaking a sweat. A typical deployment takes only a few seconds to complete. This automation spans from provisioning infrastructure to deployment of applications and configurations for monitoring dashboards and alerts. The tools we use include, but are not limited to: Terraform, Helmfile, and GitHub Actions.
Grafana, Loki, and Mimir are our weapons of choice when it comes to monitoring the performance and behavior of our platform, enabling us to automatically detect and escalate any potential issues to the affected teams.
As a technology company, we are dedicated to maintaining a modern and agile technology environment that empowers our engineers to thrive and build the future of sports betting technology.
About the Role
We’re now looking for a Data Engineer to join our distributed team. With a modern Data Platform in the middle, Data team provides solid foundations for solving a wide spectrum of business problems, as well as owns end-to-end delivery of data products. These typically require real-time data transportation/ingestion/integration, distributed processing, warehousing, (stream) analytics, and feeding data-points into other (internal) products. We support stakeholders with the timely discovery of new insights and data-driven decision-making through careful data modeling and quality assurance practices. In an ever-changing environment, the team relies heavily on (data) contract-first development and automation, minimizing mundane work, and leaving more time for solving interesting problems.
Our Data Engineers are primarily Software Engineers with a strong focus and passion for “All Things Data”. This role requires a Computer Science background, a solid understanding of Distributed Systems, Big Data tools and their internals, and familiarity with modern Data Architectures. For an analytics-focused role, emphasizing Business Intelligence, Data Warehouse modeling, ELT (DBT), and Data Analysis please stay tuned for the Analytics Engineer position opening.
Compensation
The compensation range for this role is €55,000 – €95,000 annually, depending on your skills, experience, and form of employment (employment or independent contractor). Additional perks include a new 16″ MacBook Pro or Linux laptop and 40 days of paid annual leave (including public holidays).
,[Engineering: Architect, design, and develop high-throughput, reliable, and scalable data solutions, which provide high-quality and timely data to the business. We live by the “you build it, you run it” mantra, so engineering responsibilities do not end with deployment, but span to operating and monitoring workloads in production., Collaboration: Work closely with other engineering and product teams, to deliver high-quality solutions. Perform code reviews, provide guidance, and mentor junior team members to maintain high coding standards and best practices., On-Call Support: Participate in on-call rotation to ensure the reliability and availability of our systems, and respond to incidents as needed.] Requirements: Spark, SQL, MongoDB, PostgreSQL, Python, Java, Kinesis, Degree, Flink, Data warehouses, Kafka, RabbitMQ, Data Lake, Continuous integration, Golang, Docker, Distributed computing, Communication skills, Data modelling, Argo, BI, Looker, Terraform, IaC, Grafana, Big Data, Kubernetes, GCP, dbt Tools: . Additionally: Training budget, Flat structure, Small teams, International projects.
PostgreSQL apache-flink Agile citus Terraform loki Apache Spark Computer Science Apache Kafka Data Engineering pulsar Looker MLOps BI tools Grafana Mimir Containerization DBT cloud environment apache-pulsar system-monitoring Business Intelligence (BI) Go CI/CD Data Science Python SingleStore RabbitMQ GitHub Actions Data lake benthos Software Development Engineer Data Architect helmfile Big data distributed-systems gcs SQL Kubernetes Java Prefect