Data Engineer
American Bureau of Shipping21 days ago
Knoxville, TN, USAEntry Level
Base Salary
$120k - $155k/yr
Responsibilities
- Provide technical and project support under project management supervision while delivering work on schedule, within budget, and according to customer requirements.
- Design, architect, optimize, and maintain data pipelines, lakehouse structures, and data models for analytics, reporting, and AI/ML systems.
- Develop and maintain scalable ETL/ELT workflows using cloud-native data platforms and data engineering practices.
- Ensure data quality, pipeline reliability, system performance, testing, monitoring, validation, and SLA-driven controls.
- Support project planning, task sequencing, scheduling, research, data analysis, reporting, presentations, and quality assurance.
- Build client relationships, identify opportunities for additional services, contribute to proposals, and communicate client needs.
- Mentor junior consultants and contribute to marketing activities, conferences, technical whitepapers, and professional networking.
Requirements
- Bachelor’s degree or equivalent work experience and training.
- At least 5 years of experience building data pipelines on AWS, Azure, or Google Cloud.
- Experience designing and maintaining lakehouse or data warehouse architectures, including platforms such as Databricks, Snowflake, or Redshift.
- Experience supporting AI/ML workloads through feature engineering, data preparation, or embedding pipelines.
- Background in data governance, lineage tracking, and quality monitoring in production environments.
- Proficiency in Python and SQL, with familiarity in Spark and distributed data processing.
- Experience with streaming technologies, AI/ML data systems, data governance tools, Docker, and Kubernetes.
- Strong client communication, problem-solving, root cause analysis, time management, adaptability, and independent judgment skills.
- Working knowledge of health, safety, quality, and environmental management practices, with the ability to learn the organization’s related management systems.
Tech Stack
Categories
Data Engineering