Understand the Business Problem and the Relevant Data
 · Maintain an intimate understanding of company and department strategy
 · Translate analysis requirements into data requirements
 · Identify and understand the data sources that are relevant to the business problem
 · Develop conceptual models that capture the relationships within the data
 · Define the data-quality objectives for the solution
 · Be a subject matter expert in data sources and reporting options   
                        
Architect Data Management Systems
 · Leverage understanding of the business problem and the nature of the data to select appropriate data management system (Big Data, OLTP, OLAP, etc.)
 · Design and implement optimum data structures in the appropriate data management system (Hadoop, Teradata, SQL Server, etc.) to satisfy the data requirements
 · Plan methods for archiving/deletion of information
                               
Develop, Automate, and Orchestrate an Ecosystem of ETL Processes for Varying Volumes of Data
 · Identify and select the optimum methods of access for each data source (real-time/streaming, delayed, static)
 · Determine transformation requirements and develop processes to bring structured and unstructured data from the source to a new physical data model
 · Develop processes to efficiently load the transform data into the data management system

Prepare Data to Meet Analysis Requirements
 · Work with the data scientist to implement strategies for cleaning and preparing data for analysis (e.g., outliers, missing data, etc.)
 · Develop and code data extracts
 · Follow best practices to ensure data quality and data integrity
 · Ensure that the data is fit to use for data science applications