Hyderabad, Telangana, India
Information Technology
Other
Cummins West Africa Limited
Overview
Description
Key Responsibilities:
Qualifications:
Skills:
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.
- 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.
- 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.
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