Engineering Manager, Entain

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 5+ years of experience in data engineering, with at least 2 years in a leadership or management role
• Strong experience with data warehousing solutions (e.g., AWS Redshift, Google BigQuery, Snowflake)
• Expertise in data pipeline development, ETL tools, and frameworks (e.g., Apache Airflow, Talend, Fivetran)
• Proficiency in SQL and experience with Python, Java, or Scala
• Familiarity with cloud platforms (AWS, GCP, Azure) and associated data tools (e.g., S3, Lambda, Dataflow)
• Strong knowledge of data modeling, data governance, and data security best practices
• Proven track record in managing teams, setting goals, and delivering results in an agile environment
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders

Desirable

• As an Engineering Manager, you will oversee the design, development, and maintenance of our data infrastructure and systems
• You’ll lead a talented team of data engineers, collaborating closely with data scientists, analysts, and other stakeholders to create scalable, high-performance data pipelines
• You’ll play a critical role in shaping our data strategy and ensuring the smooth and efficient flow of data across the organization
• Lead and mentor a team of data engineers, guiding them through the design and implementation of data solutions
• Manage the development, maintenance, and optimization of scalable data pipelines and ETL processes
• Collaborate with cross-functional teams to understand data requirements and ensure data availability for analysis and reporting
• Implement best practices for data governance, security, and quality assurance across the data engineering processes
• Continuously evaluate and improve data infrastructure, recommending and implementing new technologies to optimize performance and scalability
• Drive the evolution of data architecture to support advanced analytics, machine learning, and real-time data processing
• Ensure the team delivers on time, maintains high-quality standards, and supports the evolving needs of the business
• Foster a culture of collaboration, continuous learning, and innovation within the data team