Data Engineer designing and optimizing data pipelines using Databricks and Google Cloud Platform. Collaborating with analysts and scientists to deliver high - quality data products.
About the role
- Data Engineer at Cargill designing, building, and maintaining data systems using cloud technologies. Working with data pipelines and infrastructure to ensure data accessibility and usability.
Responsibilities
- Designs, builds and maintains moderately complex data systems
- Develops moderately complex data products and solutions using advanced data engineering and cloud based technologies
- Maintains and supports the development of streaming and batch data pipelines
- Reviews existing data systems and architectures
- Helps prepare data infrastructure to support the efficient storage and retrieval of data
- Implements automated deployment pipelines to improve efficiency of code deployments
- Performs moderately complex data modeling aligned with the datastore technology
Requirements
- Minimum requirement of 2 years of relevant work experience
- Familiarity with major cloud platforms (AWS, GCP, Azure)
- Experience with modern data architectures, including data lakes, data lakehouses, and data hubs
- Proficiency in data collection, ingestion tools (Kafka, AWS Glue), and storage formats (Iceberg, Parquet)
- Knowledge of streaming architectures and tools (Kafka, Flink)
- Strong background in data transformation and modeling using SQL-based frameworks and orchestration tools (dbt, AWS Glue, Airflow)
- Familiarity with using Spark for data transformation
- Proficient with programming in Python, Java, Scala, or similar languages
- Expert-level proficiency in SQL for data manipulation and optimization
- Understanding of data governance principles
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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