Atlanta, Georgia, US
47 days ago
Senior Platform Engineer - Data Discovery (Hybrid- Midtown- Atlanta, Georgia)

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

The Senior Platform Engineer, Data Discovery Platform Engineer will take the lead in building the data and analytics platform for modern business applications in the company. In this role, you will apply your in-depth knowledge of modern infrastructure and cloud software engineering practices to build, secure and maintain the core capabilities used by our data and application teams to drive business value. You will also coach and mentor junior engineers to deliver highly scalable and resilient systems using infrastructure as code across our data centers and cloud environments. This role will specifically work in the discoverability space designing and maintaining the Data Discovery Platform which consists of a metadata lake, data catalog, data mesh register, and data marketplace.  The Data Discovery Platform team will lead efforts to ensure data and data products are accessible and well-organized which will aid in better governance and compliance. 

Key Accountabilities Build the platforms, systems and infrastructure using in depth knowledge of software development and infrastructure as code practices or the Data Discovery Platform and Metadata Lake. Partner closely with Product & Engineering teams, proactively identifying feature sets and optimizations for the Data Discovery Platform and Metadata Model. Keep up-to-date with regulatory requirements that influence Data Discovery. Take the lead to design, develop, test, deploy, support and enhance the complex and varied automated infrastructure and platform components. Take the lead to drive large efforts, stories and tasks to completion. Participate in the engineering community to maintain and share relevant technical approaches and modern skills and present best code practices. Build prototypes to test new concepts and provide ideas on reusable framework and components to help promote adoption of new technologies. Independently handle complex issues with minimal supervision, while escalating only the most complex issues to appropriate staff. Works across engineering teams to plan installations and upgrades and ensures subsequent maintenance in accordance with IT controls and policies. Monitors Data Discovery Platform and Metadata Lake to achieve optimum performance levels. Collaborates with engineering teams by providing technical input for workflows and configurations relating to the access, security, and protection of data. Other duties as assigned. Qualifications Required QualificationsBachelor’s degree in Computer Science, Information Systems, or related field or equivalent experience Minimum of four years of related work experience in data engineering and operationalizing data ingestion pipelines and strong understanding of database storage concepts (data lake, relational databases, NoSQL, Graph, data warehousing). Minimum of four years of experience and proficiency in SQL, Python, Java. Experience working with RESTful APIs. Preferred QualificationsDesign, deploy and enhance moderately complex automated infrastructure and platform components Implementation or management of discoverability tools such as enterprise data catalogs, metadata lakes Knowledge of data management and governance concepts such as master data management, metadata management Knowledge of Data Mesh Principles Knowledge of data governance, compliance and security practices for data platforms Experience with CI/CD and other automation for cloud deployments Familiarity with infrastructure as code Cloud infrastructure management and use of serverless technologies (AWS preferred) Creating technical documentation Experience with networking (firewall, routing, etc) and disaster recovery methods such as high availability and scalability Experience with cloud native technologies such as Kubernetes and Docker Experience with the Hadoop stack (Preferred Impala and Kudu) Knowledge of enterprise information management processes and methodologies. Proven understanding of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution and processing (Kafka, Flink), and modern data warehouse tools sql (Snowflake, Databricks) Knowledge of secure coding practices including secrets management and vulnerability remediation Ability to perform technical deep-dives into code, networking, operating systems, and compute infrastructure. Experience with financial operations as related to the platform Anticipates and adopts innovations in business-building digital and technology applications Experience growing team capabilities through role modeling and mentoring Plans and prioritizes work to meet commitments aligned with organizational goals Creates new and better ways for the organization to be successful Solid interpersonal skills and a desire to improve the developer experience Ability to work effectively as part of a team, group and culture Ability to navigate ambiguity and work in agile ways Ability to make well-supported tradeoffs in complex situations  

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Equal Opportunity Employer, including Disability/Vet.

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