Senior Data Engineer

Posted 3mo ago

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Design and build scalable data extracts, integrations, transformations, and data models
Ensure successful deployment and provisioning of data solutions
Design and implement data architectures and applications
Gather and define requirements and translate them into technical designs
Advance data quality and build domain knowledge
Identify and recommend continuous improvement opportunities
Design and deploy a cloud data platform and pipeline
Design, build, and maintain reproducible machine-learning pipelines
Implement CI/CD for data and ML workflows
Build and maintain production-grade ML infrastructure
Ensure ML models follow best-practice governance
Design scalable data pipelines optimized for ML workloads
Establish MLOps standards, coding practices, and automation patterns

Bachelor or Master`s degree in technical discipline
5+ years of experience as a Data Engineer
Proficiency in data modeling concepts and techniques
Expertise with Databricks
Expertise with cloud data warehousing solutions such as S3, Redshift, or BigQuery
Hands-on experience building data pipelines and ETL/ELT workflows using PySpark
Advanced knowledge of Python
Advanced working SQL skills including query optimization
Ability to write, test, and debug RESTful APIs
Experience working in agile, cross-functional environments
Experience in data quality initiatives such as Master Data Management (MDM)
Experience operationalizing machine-learning models in production environments
Hands-on experience with ML tooling such as MLflow, SageMaker, Databricks ML, Kubeflow, or similar
Experience implementing CI/CD pipelines for data and ML workloads
Understanding of model lifecycle management, data versioning, feature store design, and model monitoring concepts
Experience containerizing ML workloads using Docker
Familiarity with monitoring frameworks, experiment tracking, and performance observability for ML models

Skills