Data Engineer 3
18 hours ago
Job Location: Beaverton OR (Remote)
Job Duration: 12 Months on W2
About Us:
We are the Consumer Data Engineering team (CoDE) at ***, seeking an experienced Senior Data Engineer to join our team. As a Senior Data Engineer, you will play a critical role in designing, building, and maintaining our big data infrastructure, ensuring the scalability, reliability, and performance of our data systems.
Job Summary:
We are looking for a highly skilled Senior Data Engineer with a strong background in big data engineering, cloud computing, and software development. The ideal candidate will have a proven track record of designing and implementing scalable data solutions using AWS, Spark, and Python. The candidate should have hands-on experience with Databricks, optimizing Spark applications, and building ETL pipelines. Experience with CI/CD, unit testing, and big data problem-solving is a plus.
Key Responsibilities:
• Design, build, and maintain large-scale data pipelines using AWS EMR, Spark, and Python
• Develop and optimize Spark applications and ETL pipelines for performance and scalability
• Collaborate with product managers and analysts to design and implement data models and data warehousing solutions
• Work with cross-functional teams to integrate data systems with other applications and services
• Ensure data quality, integrity, and security across all data systems
• Develop and maintain unit test cases for data pipelines and applications
• Implement CI/CD pipelines for automated testing and deployment
• Collaborate with the DevOps team to ensure seamless deployment of data applications
• Stay up to date with industry trends and emerging technologies in big data and cloud computing
Requirements:
• At least 5 years of experience in data engineering, big data, or a related field
• Proficiency in Spark, including Spark Core, Spark SQL, and Spark Streaming
• Experience with AWS EMR, including cluster management and job optimization
• Strong skills in Python, including data structures, algorithms, and software design patterns
• Hands-on experience with Databricks, including Databricks Lakehouse (advantageous)
• Experience with optimizing Spark applications and ETL pipelines for performance and scalability
• Good understanding of data modeling, data warehousing, and data governance
• Experience with CI/CD tools such as Jenkins, GitLab, or CircleCI (advantageous)
• Strong understanding of software development principles, including unit testing and test-driven development
• Ability to design and implement scalable data solutions that meet business requirements
• Strong problem-solving skills, with the ability to debug complex data issues
• Excellent communication and collaboration skills, with the ability to work with cross-functional teams
Nice to Have:
• Experience with Databricks Lakehouse
• Knowledge of data engineering best practices and design patterns
• Experience with agile development methodologies, such as Scrum or Kanban
REQUIRED:
5+ years in data engineering
Experience with AWS EMR, including cluster management and job optimization
Proficiency in Spark, including Spark Core, Spark SQL, and Spark Streaming
IDEAL CANDIDATE:
Hands on experience with Databricks and Lakehouse data
Migrating from AWS EMR to Databricks Lakehouse
Team:
Supporting the Commercial Analytics Engineering department
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