Data Analyst

Key Responsibilities:

• Conduct descriptive and diagnostic analytics on data sources.
• Apply machine learning tools on data and metadata to improve data quality.
• Identify patterns and trends in data sets.
• Create reports and dashboards on analysis results using business intelligence technologies.
• Develop data profiles for data tables and elements in the data lake.
• Create data catalog entries and ensure data catalog metadata quality.
• Analyze diverse data sets to identify data quality, coherency, and integrability issues and reduce data redundancy.
• Collaborate to develop data cleansing methods and rules.
• Assist in the creation and maintenance of documentation of key decisions, rules, controls, and processes.

Qualifications:

• 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.

Competencies:

• Action Oriented: Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
• 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.
• 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 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 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.

Skills:

• Demonstrated experience as a Data Analyst or in a related data-centric role.
• Proficiency in SQL (preferably SQL Server) for querying and manipulating data.
• Practical experience with Databricks for tasks related to data engineering, data science, and analytics.
• Experience working with Databricks Lakehouse architecture and data warehousing concepts.
• Knowledge of Azure cloud services, including Azure Data Factory and Azure SQL Database.
• Expertise in Python programming.
• Skilled in using PowerBI to create interactive reports, dashboards, and visualizations, with familiarity in SSAS models.
• Strong analytical mindset with excellent problem-solving skills and keen attention to detail.
• Good communication skills, capable of conveying complex data insights clearly to non-technical stakeholders.

Experience:

• Relevant experience preferred such as working in a temporary student employment, intern, co-op, or other extracurricular team activities.
• 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.
  • Exposure to Big Data open source.
  • Clustered compute cloud-based implementation experience.

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.