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Data Engineer - Olympia, United States - Vaco
Description
Title:
Data Engineer - Remote
Pay/Salary/Benefits/Perks:
Up to $150k/yr
Work from Home Policy:
Fully Remote
Interview Process:
Streamlined process, 3 interviews
Key Skills: 6+ years of experience in data engineering, Azure, ETL
Responsibilities:
Lead a team of engineers to develop data pipelines, ETL processes, and data storage solutions.
Provide technical guidance, mentorship, and support to team members.
Define and implement best practices, standards, and processes for data engineering.
Ensure adherence to industry standards and compliance with data governance policies.
Drive innovation and continuous improvement in data engineering practices.
Manage data infrastructure on cloud platforms such as AWS, Azure, or Google Cloud Platform.
Oversee data modeling, schema design, and data governance initiatives.
Lead troubleshooting efforts and resolve complex technical issues.
Collaborate with senior leadership to define data engineering strategy, roadmap, and priorities.
Manage projects to ensure successful delivery of data engineering projects.
Qualifications:
6+ years of experience in data engineering, with at least 2 years of experience in a leadership or managerial role.
Experience with:
Data pipelines
ETL processes
Data storage solutions
Data warehousing
Data lake houses (Databricks or Snowflake)
Cloud-based data platforms such as AWS, Azure, or Google Cloud Platform
Python or similar languages for data manipulation, scripting, and automation.
Solid understanding of data modeling, schema design, and data governance best practices.
Proven leadership and team management skills.
Excellent communication and collaboration skills, with the ability to interact effectively with technical and non-technical stakeholders.
Preferred
Qualifications:
Master's degree in a related field.
Certification in cloud computing (e.g., AWS Certified Solutions Architect, Azure Data Engineer Associate, Google Cloud Certified - Professional Data Engineer).
Strong project management skills, with experience in managing complex data engineering projects from conception to completion.Experience with:
Framewords such as Hadoop, Spark, Kafka, etc.
AWS Technologies:
RDS, Lambda, SNS, SQS, AppSync, EventBridge
Containerization and orchestration tools such as Docker and Kubernetes.