About
Key Responsibilities
Design, develop, and maintain scalable and robust data pipelines for extraction, transformation, and loading (ETL) of large datasets.
Optimize data processing jobs and database queries for maximum performance and efficiency.
Implement and manage data storage solutions, including data warehouses, data lakes, and other distributed systems.
Write clean, maintainable, and efficient code for data ingestion, processing, and analysis.
Troubleshoot and debug data pipeline issues, ensuring data quality and integrity.
Stay up-to-date with emerging data engineering technologies, tools, and best practices.
Mentor and support other team members in data engineering principles and practices.
Qualifications
Proficiency in Java, Python, Kotlin, or Scala.
Experience with big data technologies such as Spark, Hadoop, and Kafka.
Familiarity with workflow orchestration tools like Apache Airflow.
Experience with streaming data platforms like Kafka, Pulsar, Flink.
Experience with building data pipelines and assets, deployed on AWS services such as EMR, EMR Serverless, and AWS Glue.
Experience with relational and NoSQL databases.
Familiarity with version control systems (e.g., Git).
Excellent problem-solving skills and attention to detail.
Ability to work independently and as part of a team.
Strong communication skills.
Preferred Qualifications
Experience working with big data technologies (e.g., Spark, Hadoop, Flink).
Knowledge of modern data pipelines and orchestration tools (e.g., Airflow, Dagster).
Familiarity with Agile development methodologies.
Experience with data quality and testing frameworks.
Salary:
$180,000 - $240,000 USD annualized. This role will also be eligible to take part in Genius Sports Group's benefits plan.
Occasional travel may be required. Hybrid work models may differ depending on your role and location.
Let us know when you apply if you need any assistance during the recruiting process due to a disability.
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Languages
- English
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