Sr. Data Engineer

Salary: $75000 - 107000 per year Requirements: We require at least 4 years of relevant professional experience, with 5 years or more preferred. We value experience building data solutions on major cloud platforms such as AWS, GCP, or Azure. We look for hands-on expertise with modern data architecture, including data lakes, lakehouses, and data hubs, plus ingestion, governance, modeling, and observability. We prefer proven ability with data ingestion tools and storage formats such as Kafka, AWS Glue, Iceberg, and Parquet. We seek experience designing streaming data pipelines and working with tools like Kafka and Flink. We expect strong data transformation and modeling skills using SQL-based frameworks and orchestration tools such as dbt, AWS Glue, and Airflow. We value deep knowledge of modeling concepts including SCD and schema evolution. We look for strong Spark experience for data transformation, including streaming workloads, performance tuning, and troubleshooting with Spark UI. We require advanced programming ability in Python, Java, Scala, or similar languages. We expect expert-level SQL skills for data manipulation and optimization. We value DevOps experience, including code management, CI/CD, and deployment practices. We look for a strong grounding in data governance, including data quality, privacy, and security considerations. Experience with Snowflake would be advantageous. Familiarity with modern data management techniques and commodity trading analytics would be appreciated. We will not sponsor work visas for this position. Responsibilities: We design, build, and maintain complex data systems that support analysis and reporting. We ensure large data sets are processed efficiently and made available for decision-making with minimal supervision. We prepare data infrastructure to enable effective storage and retrieval. We assess and refine data formats to improve usability and access across the organization. We develop scalable, sustainable, and robust data products and solutions using advanced engineering and cloud technologies. We create and maintain streaming and batch pipelines that ingest data from multiple sources, transform it, and load it into platforms such as data lakes and data warehouses. We review existing data systems and architectures to identify opportunities for optimization. We collaborate with cross-functional data and analytics teams to gather requirements and ensure solutions meet functional and non-functional needs. We build prototypes to test new ideas and implement frameworks and architectures that strengthen data processing and advanced analytics capabilities. We develop automated deployment pipelines with appropriate governance to improve release efficiency. We perform complex data modeling aligned to the underlying datastore technology to support performance and accessibility. Technologies: Airflow AWS AWS Glue Azure CI/CD Cloud DevOps Flink GCP Support Java Kafka Python SQL Scala Security Snowflake Spark dbt UX UI Design Data Warehouse More: We are Solstice Analytics, a global leader in food and agricultural solutions committed to nourishing the world in a safe, responsible, and sustainable way. With more than 155,000 team members and over 160 years of family-company heritage, we partner with farmers and customers to source, make, and deliver essential products that help businesses grow, communities prosper, and consumers live well. Guided by our values, we put people first, aim higher, and do the right thing for today and for generations to come. This Senior Data Engineering role sits at the heart of our supply chain and supports a team focused on building modern data capabilities for analytics and reporting. We are an equal opportunity employer, including disability/veterans. last updated 25 week of 2026