
Big Data Engineer
1 week ago
Design and develop robust data processing pipelines and analytics solutions using Databricks.
Architect scalable and efficient data models and storage solutions tailored for the Databricks environment.
Collaborate with architecture and engineering teams to migrate existing solutions to Databricks.
Tune and optimize Databricks clusters and job performance to meet SLAs and evolving business needs.
Implement best practices for data governance, security, and compliance on the Databricks platform.
Guide and mentor junior engineers, offering technical support and best practice recommendations.
Stay informed about emerging data engineering trends and new features in Databricks and related technologies.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline.
5 to 8 years of overall experience in data engineering, with a minimum of 2 years focused on Databricks.
Hands-on proficiency in Python, Scala, or SQL.
Solid understanding of distributed computing principles and big data frameworks like Apache Spark.
Experience with major cloud platforms (AWS, Azure, or GCP) and their respective data services.
Demonstrated ability to build scalable and reliable data solutions in dynamic environments.
Strong analytical and problem-solving skills with high attention to detail.
Effective communication and collaboration skills within cross-functional teams.
Preferred Qualifications
Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
Understanding of DevOps practices for automating deployments and monitoring data pipelines.
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