Sr Data Quality Analyst
DESCRIPTION
GPP Database Link (https://cummins365.sharepoint.com/sites/CS38534/)
Job Summary:
Interprets data and turns it into information which can offer ways to improve how the data is used within the business, thus affecting business decisions. Gathers information from various sources and interprets patterns and trends. Reports back findings in a comprehensive study to senior leadership. Responsible for championing improvement of overall data quality and data process methods.
Key Responsibilities:
Conducts descriptive and diagnostic analytics on data sources, reviews results with senior leadership, and takes required actions. Applies machine learning and machine learning tools on data and metadata to improve data quality and provides recommendations and designs solutions to resolve issues. Identifies patterns and trends in data sets; applies statistical process controls on data. Creates complex reports and dashboards on analysis results applying advanced capabilities of business intelligence tools and technologies. Develops data profiles for data tables and elements in the data lake. Creates and evaluates data catalog entries, ensures data catalog metadata quality, and leverages data catalog information to provide guidance to product development teams. Analyzes complex and diverse data sets from multiple sources to identify data quality, coherency and integrability issues and reduce data redundancy; provides recommendations to resolve issues throughout the data lifecycle. Collaborates to develop data cleansing methods and rules. Assists in creation and maintenance of documentation of key decisions, rules, controls, processes and training material. Collaborates to integrate data analysis findings into governance solutions. Defines new methods and integrates new tools into data analysis processes. Coaches, mentors and reviews work of less experienced team members and provides guidance on problem resolution.
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RESPONSIBILITIES
Competencies:
Data Literacy - Expresses data in context, including data sources and constructs, analytical methods and applied techniques; describes the use-case application and resulting value.
Data Profiling - Assesses data issues and cleansing requirements to perform data extraction, mapping, collection, and testing; establishes good, quality data.
Data Communication and Visualization - Constructs a tale of the business problem, root cause, solution options, and opportunities through illustrating data visually, including reports and dashboards.
Data Quality - Identifies, understands and corrects flaws in data that supports effective information governance across operational business processes and decision making.
Project Management - Establishes and maintains the balance of scope, schedule and resources for a temporary effort (a "project").
Data Analytics - Discovers, interprets and communicates qualitative and quantitative data; determines conclusions relying on knowledge of business or functional frameworks; simultaneously applies statistics, data validity, data visualization, and problem solving approaches to effectively extract meaningful patterns and business insights; presents conclusions and outcomes that enable data driven business decisions.
Communicates effectively - Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.
Customer focus - Building strong customer relationships and delivering customer-centric solutions.
Tech savvy - Anticipating and adopting innovations in business-building digital and technology applications.
Balances stakeholders - Anticipating and balancing the needs of multiple stakeholders.
Action oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
Manages ambiguity - Operating effectively, even when things are not certain or the way forward is not clear.
Education, Licenses, Certifications:
College, university, or equivalent degree in relevant technical discipline, or relevant equivalent experience required. This position may require licensing for compliance with export controls or sanctions regulations.
Experience: 4-6 years of overall relevant experience required in :
- Data Quality process improvement & automationo Profilingo Validationo Monitoringo Cleansing
- Partner with EDM on DQ toolset & implementations (expert on tools)
- Coordinate MDM cleansing and validation
- Data profiling and analysis and leads data exploration
- Develop reporting mechanisms based on established KPI's using existing/standard tools
- Data Quality defect resolution
QUALIFICATIONS
- Knowledge of the latest technologies and trends in data science is highly preferred and includes:- SQL query language execution on NOSql and SQL sources- Exposure to Agile software development- Exposure to IoT technology- Data profiling tools, technologies and coding- Data Catalog tools and technologies- Business intelligence tools and technologies
- Intermediate experiences in the following are preferred:- Exposure to Big Data open source - Clustered compute cloud-based implementation experience
Job Systems/Information Technology
Organization Cummins Inc.
Role Category Hybrid
Job Type Exempt - Experienced
ReqID 2419043
Relocation Package No
Perks and Benefits
Health and Wellness
- FSA With Employer Contribution
- Health Reimbursement Account
- On-Site Gym
- HSA With Employer Contribution
- Health Insurance
- Dental Insurance
- Vision Insurance
- Life Insurance
- Short-Term Disability
- Long-Term Disability
Parental Benefits
- Non-Birth Parent or Paternity Leave
- Birth Parent or Maternity Leave
Work Flexibility
- Flexible Work Hours
- Remote Work Opportunities
Office Life and Perks
- Company Outings
- Casual Dress
Vacation and Time Off
- Leave of Absence
- Personal/Sick Days
- Paid Holidays
Financial and Retirement
- Relocation Assistance
- Performance Bonus
- Stock Purchase Program
- Pension
- 401(K) With Company Matching
Professional Development
- Mentor Program
- Shadowing Opportunities
- Access to Online Courses
- Lunch and Learns
- Tuition Reimbursement
Diversity and Inclusion