Associate IT Data Analyst

Michigan Farm Bureau Family of Companies•Waverly, MI

15h

About The Position

Associate IT Data Analyst Objective To assist data analysts with analysis, design, development, testing, and implementation of processes and systems that support data integrations, data standardization, data quality, and data governance for the Farm Bureau Insurance Companies.

Requirements

Bachelor’s degree in computer science or related field required, or equivalent experience may be considered.
Experience working with SQL and writing queries required.
Current knowledge of computer hardware, operating systems, program language(s) and tools, testing techniques and tools, program specification and interpretation required.
Working knowledge of systems design and analysis tools and techniques required.
Willingness to pursue continuing job related training and education in systems and insurance required.

Nice To Haves

One to two years’ experience as a data analyst or equivalent position preferred.
Experience working with and managing insurance data structures and processes preferred.
Experience with software for data cleansing, standardization, matching, profiling, data quality, and data governance preferred.

Responsibilities

Manage and analyze data processes, issues, and questions.
Understand the details of data processes and management.
Contribute to data quality, data governance, and MDM programs.
Serve as a team member on projects.
Provide data analysis, data profiling, and data discovery as needed.
Provide necessary documentation around data mapping, transformations, technical specs, and data catalog updates.
Apply principals of data, insurance, governance, and processing requirements.
Correct and identify permanent solutions to data problems.
Take calls outside of standard working hours to issue diagnosis and resolution in both proactive and reactive modes.
Develop, use, and maintain automated tools and processes.
Follow established change management processes for changes.
Gain knowledge of corporate data asset repositories, structures, and metadata (ODS, EDW, MDM (Profisee), Guidewire, Data Lake, Customer Registry, data marts, etc.).
Learn the relationship of the data within each source as well as cross sources.