Data Engineer

at  Archer Daniels Midland Company

JOB DESCRIPTION

Data Engineer – Data Analyst
This is an exempt level position.
Summary:
Data Engineer/Analyst will work on designing, building, and implementing a data foundation to support a strategic analytics project that drives strategic growth for ADM. This involves liaising with functional teams that build or acquire the underlying data, application owners to understand raw or source data structures, and end users to accurately design strategic data marts. Finally, designing and building data pipelines, ETL/ELT integrations, constructing and modifying data marts, preparing (cleaning, transforming) data, and collaborating with extended team members to design impactful business solutions. Data Engineer needs to have specifically expert technical knowledge of Python, AzureAI and RAG and platforms and software technology (ETL/ELT, SQL, PySpark, Power BI, Python), deep expertise in data management techniques, ability to drive effective support of data analysis and model management, and experience with IT project management practices

Responsibilities:

• Standardize data and reporting across businesses and teams to enable consistency and quality of key business data
• Design and develop enterprise data warehouse platform that conforms to consistent methodologies, standards and industry best practices
• Design, develop, test and document data integrations and assist with deployment, validation and hypercare
• Maintain and support Azure integrations like ADF, Synapse and AI using technical documentation
• Participate in designing overall logical & physical data warehouse and data mart models and architectures to support business requirements
• Develop and maintain SQL, PL/SQL, PySpark, Python code as needed
• Assist with review to confirm technical feasibility of integration development objects based on integration principles and best practices
• Understand and navigate a wide array of source data systems (enterprise data warehouses, relational databases, IT systems, in house and COTS applications, documents, APIs, unstructured data, big data, Vector database etc.)
• Analyze data and assist with developing insights (e.g., via data visualization tools like Power BI / SAC) to enable business decision making
• Propose new methodologies to demonstrate data to improve existing methodologies
• Developing prototypes and proof of concepts for required solutions
• Implementing information security standards in enterprise data warehouse
• Prepare and present ideas and recommendations to colleagues and management
• Document solutions through high/low level design documentation
• Learn new groundbreaking data science and analytic tools as needed
• Contribute to development of the overall solution approach
• Recommend solutions to address gaps
• Assist with development estimation
• Supervise and review activities of consultants

Requirements:

• 4-year Bachelor’s degree or equivalent in IT, Computer Science, Science, Engineering, Statistics, Programming, Business Analytics, Mathematical or related field
• At least 6 years of enterprise BI and Analytics technical experience implementing data warehouse and data marts in an Agile environment
• 5 years of recent experience using data integration, ETL, ELT, data replication, and data warehouse automation tools such as Qlik Replicate, Microsoft Azure Data Factory, Databricks and Microsoft SQL Server Integration Services
• 5 years of recent experience in data processing using SQL, PySpark, Python
• Experience sourcing data from ERP data sources, e.g., SAP, JD Edwards, PeopleSoft, Oracle EBS in support of analytic product development and business transformation projects
• Experience with MPP systems, Azure Synapse, ML and AI preferred
• Experience with databases like SAP HANA,SQLMI, Synapse
• Experience in delivering Cloud based Data Solutions in Azure
• Experience with Data Virtualization technologies and tools, Denodo preferred
• Working knowledge of BI architecture, dimensional modeling, data warehousing best practices, and data integration standard methodologies
• Experience in delivering solutions using iterative development methodologies like Agile, KanBan, DevOps
• Experience working with Big Data technologies such as PySpark, Kafka, DataBricks, Hive, or equivalent
• Experience with visualization technologies and services including Microsoft Power BI and SAP Analytics Cloud is plus.
• Working knowledge of Python ML libraries like Scikit-learn/PyTorch or Azure ML
• Experience working in DevOps / CICD framework
• High accountability with a demonstrated ability to deliver
• Strong communication skills including design documentation
• Strong collaboration skills working with architecture, design and development teams

• Standardize data and reporting across businesses and teams to enable consistency and quality of key business data
• Design and develop enterprise data warehouse platform that conforms to consistent methodologies, standards and industry best practices
• Design, develop, test and document data integrations and assist with deployment, validation and hypercare
• Maintain and support Azure integrations like ADF, Synapse and AI using technical documentation
• Participate in designing overall logical & physical data warehouse and data mart models and architectures to support business requirements
• Develop and maintain SQL, PL/SQL, PySpark, Python code as needed
• Assist with review to confirm technical feasibility of integration development objects based on integration principles and best practices
• Understand and navigate a wide array of source data systems (enterprise data warehouses, relational databases, IT systems, in house and COTS applications, documents, APIs, unstructured data, big data, Vector database etc.)
• Analyze data and assist with developing insights (e.g., via data visualization tools like Power BI / SAC) to enable business decision making
• Propose new methodologies to demonstrate data to improve existing methodologies
• Developing prototypes and proof of concepts for required solutions
• Implementing information security standards in enterprise data warehouse
• Prepare and present ideas and recommendations to colleagues and management
• Document solutions through high/low level design documentation
• Learn new groundbreaking data science and analytic tools as needed
• Contribute to development of the overall solution approach
• Recommend solutions to address gaps
• Assist with development estimation
• Supervise and review activities of consultant