Cargill

Data Engineer

Cargill$95K — $115K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 2-3 years of relevant work experience required.
  • Proficiency in Python, SQL, or similar programming languages, with expert-level SQL skills.
  • Experience using Snowflake for data tasks.
  • Familiarity with SAP or similar enterprise platforms.
  • DevOps practices expertise, including CI/CD and code management.

Responsibilities

  • Develop and maintain advanced data products and solutions using cloud technologies.
  • Support the creation and management of data pipelines for seamless data ingestion and processing.
  • Review and enhance existing data systems for optimization and improvement.
  • Prepare data infrastructure for efficient data storage and retrieval.
  • Implement data formats for improved usability across the organization.
  • Collaborate with cross-functional teams to gather requirements for data solutions.
  • Build prototypes and frameworks to test new data processing concepts.

Benefits

  • Health, dental, and vision insurance.
  • 401(k) retirement plan with company match.
  • Generous paid time off policy.
  • Professional development opportunities.
  • Flexible working arrangements.
Full Job Description
Job Purpose and Impact

  • The Professional, Data Engineering job designs, builds and maintains moderately complex data systems that enable data analysis and reporting. With limited supervision, this job collaborates to ensure that large sets of data are efficiently processed and made accessible for decision making.


Key Accountabilities

  • DATA & ANALYTICAL SOLUTIONS: Develops moderately complex data products and solutions using advanced data engineering and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.
  • DATA PIPELINES: Maintains and supports the development of streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others.
  • DATA SYSTEMS: Reviews existing data systems and architectures to implement the identified areas for improvement and optimization.
  • DATA INFRASTRUCTURE: Helps prepare data infrastructure to support the efficient storage and retrieval of data.
  • DATA FORMATS: Implements appropriate data formats to improve data usability and accessibility across the organization.
  • STAKEHOLDER MANAGEMENT: Partners with multi-functional data and advanced analytic teams to collect requirements and ensure that data solutions meet the functional and non-functional needs of various partners.
  • DATA FRAMEWORKS: Builds moderately complex prototypes to test new concepts and implements data engineering frameworks and architectures to support the improvement of data processing capabilities and advanced analytics initiatives.
  • AUTOMATED DEPLOYMENT PIPELINES: Implements automated deployment pipelines to support improving efficiency of code deployments with fit for purpose governance.
  • DATA MODELING: Performs moderately complex data modeling aligned with the datastore technology to ensure sustainable performance and accessibility.


Qualifications

  • Minimum requirement of 2 years of relevant work experience. Typically reflects 3 years or more of relevant experience.


Preferred Qualifications
  • EXPERIENCE: Professional experience as Software Engineer
  • PROGRAMMING: Proficient with programming in Python, SQL, or similar languages. Expert-level proficiency in SQL for data manipulation and optimization.
  • DATA & ANALYTICS TOOLS: Snowflake
  • SOFTWARE: Experience working with SAP or similar enterprise software platforms.
  • DEVOPS: Demonstrated experience in DevOps practices, including code management, CI/CD, and deployment strategies.


The business will not sponsor applicants for work visa for this position.

About Cargill

Industry
Founded
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