Senior Data Engineer ‎- Atlanta, GA

Description

Summary: This Senior Professional, Data Engineering job designs, builds, and maintains complex data systems to enable data analysis and reporting, ensuring efficient processing and accessibility for decision making. Highlights: 1. Develops complex data products using advanced engineering and cloud technologies 2. Builds and maintains streaming and batch data pipelines for seamless ingestion 3. Collaborates with multi-functional teams to ensure data solutions meet needs Apply Now 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 th 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 alternive fuel. Our 160,000 colleagues, opering in 70 countries, make essential products th touch billions of lives each day. Join us and reach your higher purpose Cargill. Job Summary The Senior Professional, Da Engineering job designs, builds and maintains complex da systems th enable da analysis and reporting. With minimal supervision, this job ensures th large sets of da are efficiently processed and made accessible for decision making.  Key Accountabilities DATA INFRASTRUCTURE: Prepares da infrastructure to support the efficient storage and retrieval of da.  DATA FORMATS: Examines and resolves approprie da forms to improve da usability and accessibility across the organizion.  DATA & ANALYTICAL SOLUTIONS: Develops complex da products and solutions using advanced engineering and cloud-based technologies, ensuring they are designed and built to be scalable, sustainable and robust.  DATA PIPELINES: Develops and maintains streaming and bch da pipelines th facilite the seamless ingestion of da from various da sources, transform the da into informion and move to da stores like da lake, da warehouse and others.  DATA SYSTEMS: Reviews existing da systems and architectures to identify areas for improvement and optimizion.  STAKEHOLDER MANAGEMENT: Collabores with multi-functional da and advanced analytic teams to gain requirements and ensure th da solutions meet the functional and non-functional needs of various partners.  DATA FRAMEWORKS: Builds complex prototypes to test new concepts and implements da engineering frameworks and architectures th improve da processing capabilities and support advanced analytics initiives.  AUTOMATED DEPLOYMENT PIPELINES: Develops automed deployment pipelines improving efficiency of code deployments with fit for purpose governance.  DATA MODELING: Performs complex da modeling in accordance to the dastore technology to ensure sustainable performance and accessibility.  Qualificions Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience. Preferred Qualificions: CLOUD ENVIRONMENTS: Experience developing da systems on major cloud plforms (AWS, GCP, Azure).  DATA ARCHITECTURE: Hands-on experience building modern da architectures, including da lakes, da lakehouses, and da hubs, along with reled capabilities such as ingestion, governance, modeling, and observability.  DATA INGESTION: Demonstred proficiency in da collection, ingestion tools (Kafka, AWS Glue), and storage forms (Iceberg, Parquet).  DATA STREAMING: Experience developing da pipelines with streaming architectures and tools (Kafka, Flink).  DATA MODELING: Expertise in da transformion and modeling using SQL-based frameworks and orchestrion tools (dbt, AWS Glue, Airflow). Deep experience with modeling concepts like SCD and schema evolution.  DATA TRANSFORMATION: Strong background with using Spark for da transformion, including streaming, performance tuning, and debugging with Spark UI.  PROGRAMMING: Advanced programming skills in Python, Java, Scala, or similar languages. Expert-level proficiency in SQL for da manipulion and optimizion.  DEVOPS: Demonstred experience in DevOps practices, including code management, CI/CD, and deployment stregies.  DATA GOVERNANCE: Strong background in da governance principles, including da quality, privacy, and security considerions for da product development and consumption.  The business will not sponsor applicants for work visas for this position. #LI-NS7 #Standard Equal Opportunity Employer, including Disability/Vet. Apply Now