Data Engineer II, Enterprise Analytics

Requirements

• Bachelor’s Degree in STEM related field or equivalent
• Eight years of related experience
• Experience with building robust data pipelines and working with large-scale datasets.
• Highly proficient use of tools, techniques, and manipulation including Cloud platforms, programming languages, and a full understanding of modern engineering practices.
• Proficiency in tools like AWS, Databricks, Snowflake, Ab Initio, Terraform etc.
• Passion for automation, optimization and delivering high-quality data solutions.
• The ability to deliver work at a steady, predictable pace to achieve commitments, deliver complete solutions but release them in small batches, and identify and negotiate important tradeoffs.
• Demonstrated track record of domain expertise including understanding technical concepts necessary and industry trends and possess in-depth knowledge of immediate systems worked on and some knowledge of adjacent systems.
• Strong problem solver who ensures systems are built with longevity and creates innovate ways to resolve issues.
• Strong written and verbal communication skills with the ability to work collaborate well with team members and business partners.
• Ability to lead team members and help create a safe environment for others to learn and grow as engineers.
• and a proven track record of self-motivation in identifying opportunities and tracking team efforts.
• Experience with some of the following tools & platforms (or similar): AWS (S3, Lambda, Kinesis, API Gateway, IAM, Glue, SNS, SQS, EventBridge, EKS, VPC, Step Functions, ECS/EKS, DynamoDB, etc.), Databricks, Python, JavaScript, Kafka, dbt, Terraform, Snowflake, SQL, Jenkins, GitHub, Airflow, Alation, Secrets Management (HashiCorp Vault, AWS Secrets Manager, or similar), Docker / OpenShift / Open Cloud Foundry, MongoDB, SonarQube
• Knowledge and experience with the some of the following concepts: Real-time & Batch Data Processing, Workload Orchestration, Cloud, Data lakes, Data Security, Networking, Serverless, Testing/Test Automation (Unit, Integration, Performance, etc.), DevOps, Logging, Monitoring, and Alerting, Containerization, Encryption / Decryption, Data Masking, Cost & Performance Optimization
• What is a Must Have? Bachelor’s degree or equivalent training with data tools, techniques, and manipulation.
• Four years of data engineering or equivalent experience.