Data Engineering Lead

At Intellias, we're always on the lookout for exceptional talent to join our team in Spain. Over 20 years of market experience, Intellias brings together technologists, creators and innovators in Europe, North and Latin America, and the Middle East. Join our international team and take the mission to solve the advanced tech challenges of tomorrow!

If you're enthusiastic about contributing your skills and experience to our organization, we invite you to submit your CV for this position.

What we offer you in Spain

• Permanent employment contract with Intellias Spain
• Private medical insurance, complementing the public healthcare system
• Flexible benefits plan through Pluxee, including:

Tax-saving advantages (up to 30% of your gross salary)

• Access to a corporate discount platform, with offers from over 200 top brands
• Full access to all benefits from day one

Requirements:

• 5+ years of hands-on experience in data engineering, including expertise in Python, Scala, or Java.
• Deep understanding of Apache Kafka for stream processing workflows (required)
• Proficiency in managing and optimizing databases such as PostgreSQL, MySQL, MSSQL.
• Familiarity with analytical databases.
• Familiarity with both cloud solutions (AWS preferably) and on-premises environments as part of cost-optimization efforts.
• Experience with ClickHouse or similar technology.
• Knowledge of additional data tools and frameworks such as Flink, Redis, RabbitMQ, Superset, Cube.js, Minio, and Grafana (optional but beneficial).
• Strong leadership and mentoring skills, with the ability to guide a team and provide technical direction.
• Experience ensuring system reliability, scalability, and data integrity through best practices.
• Familiarity with iGaming industry terminology and challenges is highly preferred.

As a team member you will:

• Provide technical leadership, including making key decisions on solution design, architecture, and implementation strategies.
• Lead and mentor a team of data engineers, serving as the primary point of contact for technical guidance.
• Design and oversee the implementation of scalable, efficient data pipelines and architectures, with a strong focus on stream processing.
• Develop and maintain robust data storage and processing solutions, leveraging tools like Apache Kafka, Redis, and ClickHouse.
• Guide the migration of selected cloud-based solutions to on-premises tools, optimizing costs while maintaining performance and reliability.
• Collaborate with stakeholders to gather requirements, propose designs, and align data strategies with business objectives.
• Ensure system reliability and scalability, with a focus on high availability and robust data transfer mechanisms (e.g., "at least once" delivery).
• Stay up-to-date with emerging technologies and evaluate their potential application to improve the overall data ecosystem.