Data Quality Analyst

Key Responsibilities

• Serve as an expert on data quality tools.
• Manage metadata and data standards to ensure adherence, working closely with IT.
• Develop and maintain rules to support a robust data quality process.
• Use Key Performance Indicators (KPIs) to measure data quality.
• Assist with tracking, research, and analytical support; provide input to the design and development of project plans.
• Maintain documentation, notes, databases, and other records; communicate the state of data quality.
• Assist with managing project risk using quality tools to identify areas of risk.
• Identify and track data quality issues; create and execute action plans for resolution.
• Escalate issues and critical conflicts in a timely fashion.
• Document and share team learnings with other teams; draw on other experiences to enhance the success of the project.
• Help the business to prepare data.
• Assist with initial data exploration steps (binning, pivoting, summarizing, and finding correlations).
• Assist with cataloguing business attributes to enable data discovery.
• Support business to establish and enforce guidelines for data collection, integration, and processes.
• Perform data and systems analysis as required to support data governance processes.
• Understand data governance roles and processes, and ensure they are followed.
• Assist with preparation of communications to leaders and stakeholders.

Qualifications:

• B.Tech/BE in Computer Science, IT, or a relevant field.
• College, university, or equivalent degree in a relevant technical discipline, or equivalent experience required.

Competencies:

• Collaborates - Building partnerships and working collaboratively with others to meet shared objectives.
• 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.
• Interpersonal savvy - Relating openly and comfortably with diverse groups of people.
• Data Analytics - Discovering, interpreting, and communicating qualitative and quantitative data; determining conclusions relying on knowledge of business or functional frameworks; simultaneously applying statistics, data validity, data visualization, and problem-solving approaches to effectively extract meaningful patterns and business insights; presenting conclusions and outcomes that enable data-driven business decisions.
• Data Mining - Extracting insights from data by identifying relationships and patterns through a suite of data exploration and data visualization techniques to understand the underlying structure of the data and enable sound conclusions upon model building.
• Data Modeling - Creating, writing, and testing data models, test scripts, and build scripts using industry standards and tools, version control, and build and test automation to meet business, technical, security, governance, and compliance requirements.
• Data Communication and Visualization - Constructing a tale of the business problem, root cause, solution options, and opportunities through illustrating data visually, including reports and dashboards.
• Data Governance - Assuring definition, ownership, metadata management, and security for Cummins data.
• Data Literacy - Expressing data in context, including data sources and constructs, analytical methods, and applied techniques; describing the use-case application and resulting value.
• Data Profiling - Assessing data issues and cleansing requirements to perform data extraction, mapping, collection, and testing; establishing good, quality data.
• Data Quality - Identifying, understanding, and correcting flaws in data that supports effective information governance across operational business processes and decision-making.
• Values differences - Recognizing the value that different perspectives and cultures bring to an organization.

Knowledge/Skills:

Technical Skills

• Power BI
  • Develop, design, and maintain interactive Power BI dashboards and reports.
  • Connect and integrate data from various sources like SQL databases, APIs, and cloud services.
  • Implement DAX functions for data transformation and advanced calculations.
  • Optimize Power BI performance and manage data refresh schedules.
• Python
  • Utilize Python libraries (such as Pandas, NumPy, Matplotlib, and Seaborn) for data manipulation and analysis.
  • Conduct exploratory data analysis (EDA) to uncover insights and trends.
  • Develop scripts for data cleaning, preparation, and visualization.
  • Use Python for automating data processing and analysis workflows.
  • Implement machine learning algorithms (supervised and unsupervised) using libraries like Scikit-learn.
• Power Apps Development
  • Design and develop custom Power Apps applications to meet business requirements.
  • Integrate Power Apps with Power Automate, SharePoint, and other Microsoft services.
  • Troubleshoot and optimize existing Power Apps solutions.
• SQL Development & Database Management
  • Write, optimize, and manage complex SQL queries, stored procedures, and views.
  • Ensure data integrity, performance tuning, and database security.
  • Work on ETL processes for data extraction, transformation, and loading.
• Automation & Integration
  • Leverage Power Automate to automate workflows and data processes.
  • Integrate Power BI and Power Apps with external systems.
• Basic Statistics
  • Perform statistical analysis and hypothesis testing.
  • Use statistical methods to interpret and analyze data trends.
• Collaboration & Documentation
  • Work closely with business stakeholders to gather and understand requirements.
  • Document data models, report structures, and Power Apps solutions.
  • Provide training and support to end users.

Experience:

• 1-3 years of hands-on experience with Power BI, Power Apps, and SQL.

Cummins is an equal opportunity employer. Our policy is to provide equal employment opportunities to all qualified persons without regard to race, sex, color, disability, national origin, age, religion, union affiliation, sexual orientation, veteran status, citizenship, gender identity, or other status protected by law.