Staff Data Engineer, Blitz

• Bachelor's with equivalent experience or Master's degree in Computer Science, Engineering, or a related field
• Minimum of 5 years of experience in data engineering
• Proven experience with Airflow, DBT, and Databricks is required
• Proficiency in programming languages such as Python, Scala, or Java
• Strong knowledge of SQL and experience with relational databases and data warehousing solutions
• Expertise in designing and optimizing ETL processes and data workflows
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop) is a plus
• Excellent problem-solving skills with a strong attention to detail
• Strong communication and interpersonal skills
• Ability to work independently and collaboratively in a fast-paced, dynamic environment
• A proactive attitude towards learning and adapting to new technologies
• Strong data analysis skills
• Passionate about understanding player behavior within game
• Experience with Postgres and building structured tables

Desirable

• As a Staff Data Engineer II at Blitz you will be responsible for designing, developing, and maintaining robust data pipelines and infrastructure
• You will work closely with data scientists, analysts, and other engineers to ensure the efficient collection, processing, and storage of data
• Your expertise in Airflow, DBT, and Databricks will be essential in optimizing our data workflows and enabling advanced analytics and insights
• Data Pipeline Development:
• Design, build, and maintain scalable data pipelines using Airflow to orchestrate complex workflows
• Implement data transformations and cleaning processes using DBT (Data Build Tool) to ensure data quality and consistency
• Data Integration and Management:
• Integrate diverse data sources, ensuring seamless data flow and accessibility across the organization
• Develop and manage data models, schemas, and storage solutions in Databricks to support analytical and operational use cases
• Performance Optimization:
• Optimize data processing performance, ensuring low latency and high reliability
• Monitor and troubleshoot data pipeline issues, implementing solutions to improve efficiency and reduce downtime
• Collaboration and Communication:
• Collaborate with data scientists, analysts, and business stakeholders to understand data needs and translate them into technical requirements
• Document data engineering processes, standards, and best practices for knowledge sharing and future reference
• Innovation and Best Practices:
• Stay up-to-date with the latest trends and technologies in data engineering and recommend improvements to our data infrastructure
• Mentor and provide guidance to junior data engineers, fostering a culture of continuous learning and improvement