Sr. Azure Data Engineer

Medline Industries, LP•Northbrook, IL

1d•$101,000 - $152,000

About The Position

Translate business requirements into the appropriate data models that integrate with the overall logical data warehouse. Define business data requirements and create logical and physical data models. Assist as needed in the design and development of ETL standards, policies, procedures, and metadata to ensure accuracy, quality, integrity, and optimization of this information. - Create/maintain the Enterprise Business Intelligence data architecture to increase the robustness, performance, and scalability of systems. Ensure optimal end user performance by establishing and consistently executing overall system performance assessment processes and associated action plans. Create conceptual, logical and physical database models as well as process and data lineage diagrams. Create Application design, High level Design based on customer requirements. - Provide oversight and direction for the design and development of the data layer(s). Develop logical data models and physical data base designs applied across multiple computing environments. Maintain quality of data in the warehouse, ensuring: integrity of data in the warehouse, correcting any data problems, data currency, establish design procedures to purge/archive old data - Assist development team in the design of new BI solutions. Work with product owner and business users to understand and translate user stories and/or requirements into data models, analytics reports and scenario models. Work closely with ETL developers to assist them with development life cycle. - Lead technology review meetings and ensure appropriate governance processes are followed. Ensure that documentation is created, meets standards, and is properly maintained according to established standards and procedures, to facilitate ongoing support and maintenance. Provide technical leadership and guide team members. - Develop standards, process flows and tools that promote and facilitate the mapping of data sources, documenting interfaces and datamovement across the enterprise. Ensure design meets the requirements. Source data from legacy systems that are to be loaded into the warehouse; provide extracts of data from the warehouse back to operational systems. - Provide architectural solutions covering data structures, sourcing, integration, security, and retention. - Define governance and best practices around meta-data to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, reusability, and consistent definitions for common reference data. Medline offers a business casual, entrepreneurial work environment with strong growth potential, a competitive compensation package, and a complete benefits package including medical/dental/vision/life insurance; 401(k) with company match. And much more!

Requirements

Bachelor’s degree
Minimum 4 years of experience in consulting or similar analyst position implementing DW’s and Data Marts.
Proven experience with ETL tool either SSIS, Informatica or DataStage.
Experience working with data warehouses.
Professional or educational experience in software development.
Excellent communication, and data analysis skills
Excellent knowledge of SQL for performing data analysis
Proficient in MS Office suite (Word, Excel, PowerPoint, Access, Visio) software

Nice To Haves

Advanced Analytical Thinking and Problem Solving skills
Solid experience in architecture, advanced reporting and dashboards.
Strong SQL skills and experience with performance tuning are required.
Superior Communication and Business-Technical Interaction skills.
Good understanding of Data Modeling concepts, Data relationships.
Knowledgeable with ETL technologies SSIS, Informatica or DataStage.

Responsibilities

Translate business requirements into the appropriate data models that integrate with the overall logical data warehouse.
Define business data requirements and create logical and physical data models.
Assist as needed in the design and development of ETL standards, policies, procedures, and metadata to ensure accuracy, quality, integrity, and optimization of this information.
Create/maintain the Enterprise Business Intelligence data architecture to increase the robustness, performance, and scalability of systems.
Ensure optimal end user performance by establishing and consistently executing overall system performance assessment processes and associated action plans.
Create conceptual, logical and physical database models as well as process and data lineage diagrams.
Create Application design, High level Design based on customer requirements.
Provide oversight and direction for the design and development of the data layer(s).
Develop logical data models and physical data base designs applied across multiple computing environments.
Maintain quality of data in the warehouse, ensuring: integrity of data in the warehouse, correcting any data problems, data currency, establish design procedures to purge/archive old data
Assist development team in the design of new BI solutions.
Work with product owner and business users to understand and translate user stories and/or requirements into data models, analytics reports and scenario models.
Work closely with ETL developers to assist them with development life cycle.
Lead technology review meetings and ensure appropriate governance processes are followed.
Ensure that documentation is created, meets standards, and is properly maintained according to established standards and procedures, to facilitate ongoing support and maintenance.
Provide technical leadership and guide team members.
Develop standards, process flows and tools that promote and facilitate the mapping of data sources, documenting interfaces and datamovement across the enterprise.
Ensure design meets the requirements.
Source data from legacy systems that are to be loaded into the warehouse; provide extracts of data from the warehouse back to operational systems.
Provide architectural solutions covering data structures, sourcing, integration, security, and retention.
Define governance and best practices around meta-data to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, reusability, and consistent definitions for common reference data.