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Cargill’s size and scale allows us to make a positive impact in the world. Our purpose is to nourish the world in a safe, responsible and sustainable way. We are a family company providing food, ingredients, agricultural solutions and industrial products that are vital for living. We connect farmers with markets so they can prosper. We connect customers with ingredients so they can make meals people love. And we connect families with daily essentials — from eggs to edible oils, salt to skincare, feed to alternative fuel. Our 160,000 colleagues, operating in 70 countries, make essential products that touch billions of lives each day. Join us and reach your higher purpose at Cargill.

Job Purpose and Impact

As a Senior Data Engineer Tech Lead at Cargill you will provide day to day technical leadership to a team working across the full stack to design, develop and operate complex high performance and data centric solutions using our comprehensive and modern data capabilities and platforms. You and your team members will play a critical role in enabling analytical insights and process efficiencies for Cargill’s diverse and complex business environments. You will work in a small team that shares your passion for building innovative, resilient, and high-quality solutions while sharing, learning and growing together.

Key Accountabilities

• Collaborate with business stakeholders, product owners and across your team to define requirements design product or solutions.

• Participate in the decision making process related to architecting products solutions.

• Develop technical products or solutions utilizing big data and cloud based technologies and ensure they are designed and built to be scalable, sustainable and robust.

• Perform complex data modeling and prepare data in databases for use in various analytics tools and to configurate and develop data pipelines to move and optimize data assets.

• Provide necessary technical guidance through all phases of product or solution life cycle.

• Build complex prototypes to test new concepts and develop ideas on reusable frameworks, components and data products or solutions.

• Help drive the adoption of new technologies and methods within the data engineering team and be a role model and mentor for data engineers.

• Independently solve complex issues with minimal supervision, while escalating more complex issues to appropriate staff.

• Other duties as assigned

Qualifications

Minimum Qualifications

• Bachelor's degree in a related field or equivalent experience

• Minimum of four years of related work experience

Preferred Qualifications

• Experience developing modern data architectures, such as data warehouses, data lakes, data meshes, hubs and associated capabilities including ingestion, governance, modeling, observability and more.

• Experience with data collection and ingestion capabilities, such as AWS Glue, Kafka Connect, Flink and others.

• Experience with data storage and management of large, heterogenous datasets, including formats, structures, and cataloging with such tools as Iceberg, Parquet, Avro, ORC, S3, HFDS, HIVE, Kudu or others.

• Experience with transformation and modeling tools, including SQL based transformation frameworks, orchestration and quality frameworks such as dbt, Apache Nifi, Talend, AWS Glue, Airflow, Dagster, Great Expectations, Oozie and others

• Experience working in Big Data environments including tools such as Hadoop and Spark

• Experience working in Cloud Platforms such as AWS, GCP or Azure

• Experience of streaming and stream integration or middleware platforms, tools, and architectures such as Kafka, Flink, JMS, or Kinesis.

• Strong programming knowledge of SQL, Python, R, Java, Scala or equivalent

• Proficiency in engineering tooling such as docker, git, and container orchestration services

• Strong experience of working in devops models with demonstratable understanding of associated best practices for code management, continuous integration, and deployment strategies.

• Experience with indirect and direct leadership of engineering teams

• Experience and knowledge of data governance considerations including quality, privacy, security associated implications for data product development and consumption.

• Excellent analytical and problem-solving skills

• Excellent communication skills with technical and non-technical stakeholders

• Able to bring a systems thinking / systems mindset to problem solving

• A passion for quality with an owners mindset

• A curious learner

• Ability to work effectively as part of a team, group and culture

• Ability to navigate ambiguity and work in agile ways

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Equal Opportunity Employer, including Disability/Vet.