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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
Full Time
Consumer Goods
$113k-139k (estimate)
01/24/2024
02/04/2025
adm.com
CHICAGO, IL
15,000 - 50,000
1902
Public
JUAN R LUCIANO
>$50B
Consumer Goods
ADM processes cereal grains and oilseeds into products used in food, beverage, nutraceutical, industrial and animal feed markets.
The job skills required for Data Engineer include SQL, Python, Data Engineering, Big Data, Data Warehouse, Computer Science, etc. Having related job skills and expertise will give you an advantage when applying to be a Data Engineer. That makes you unique and can impact how much salary you can get paid. Below are job openings related to skills required by Data Engineer. Select any job title you are interested in and start to search job requirements.
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The data engineer develops and maintains the enterprise data framework for continued use.
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A data engineer prepares data for analytical or operational uses.
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Data Engineers are the technical professionals who prepare data that can be used by data scientists for valuable decisions and strategies.
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