Data Engineer 4

4 days ago

Beaverton, United States Sunrise Systems, Inc. Full time
  Job Title: Data Engineer 4
Reference ID: 24-04506
Client Location: Beaverton, OR
Duration: 2 years
Job Type: Contract (Candidates must be able to work on W2 without VISA sponsorship)
 
Our client, a leading sporting goods & apparel manufacturing company, is looking for Data Engineer 4
 
Preferred candidate from Beaverton, OR
If Remote, must work PST hours - please confirm in notes willingness to work PST hours
 
Description:  
  • Bachelor’s degree or higher or combination of relevant education, experience, and training in Computer Science.
  • 6+ years experience in Data Engineering.
  • 4+ years of experience working with Python specifically related to data processing with proficiency in Python Libraries - Pandas, NumPy, PySpark, PyOdbc, PyMsSQL, Requests, Boto3, SimpleSalesforce, Json.
  • 3+ years of experience in Data Warehouse technologies – Databricks and Snowflake.
  • Strong Data Engineering Fundamentals (ETL, Modelling, Lineage, Governance, Partitioning & Optimization, Migration).
  • Strong Databricks-specific skills (Apache Spark, DB SQL, Delta Lake, Delta Share, Notebooks, Workflows, RBAC, Unity Catalog, Encryption & Compliance).
  • Strong SQL (SQL, performance, Stored Procedures, Triggers, schema design) skills and knowledge of one of more RDBMS and NoSQL DBs like MSSQL/MySQL and DynamoDB/MongoDB/Redis.
  • Cloud Platform Expertise: AWS and/or Azure.
  • Experience in one or more ETL tools like Apache Airflow/AWS Glue/Azure Data Factory/Talend/Alteryx.
  • Excellent knowledge of coding and architectural design patterns.
  • Passion for troubleshooting, investigation and performing root-cause analysis.
  • Excellent written and verbal communication skills.
  • Ability to multitask in a high energy environment.
  • Agile methodologies and knowledge of Git, Jenkins, GitLab, Azure DevOps and tools like Jira/Confluence.
 
Nice to have:
  • Tools like - Collibra, Hackolade.
  • Migration Strategy and Tooling
  • Data Migration Tools: Experience with migration tools and frameworks or custom-built solutions to automate moving data from Snowflake to Databricks.
  • Testing and Validation: Ensuring data consistency and validation post-migration with testing strategies like checksums, row counts, and query performance benchmarks
 
 

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