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