Senior, Data Analyst
About The Position
What you'll do... Position: Senior, Data Analyst Job Location: 2608 SE J St, Bentonville, AR 72716 Duties: Tech. Problem Formulation: Translate/co-own business problems within one's discipline to data related or mathematical solutions. Identify appropriate methods/tools to be leveraged to provide a solution for the problem. Share use cases and give examples to demonstrate how the method would solve the business problem. Demonstrate up-to-date expertise and apply this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; support and align efforts to meet customer and business needs; and build commitment for perspectives and rationales. Understanding Business Context: Provide recommendations to business stakeholders to solve complex business issues. Develop business cases for projects with a projected return on investment or cost savings. Translate business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serve as interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Provide and support the implementation of business solutions by building relationships and partnerships with key stakeholders; identify business needs; determine and carry out necessary processes and practices; monitor progress and results; recognize and capitalize on improvement opportunities; and adapt to competing demands, organizational changes, and new responsibilities. Data Source Identification: Support the understanding of the priority order of requirements and service level agreements. Help identify the most suitable source for data that is fit for purpose. Perform initial data quality checks on extracted data. Data Visualization: Generate appropriate graphical representations of data and model outcomes. Understand customer requirements to design appropriate data representation for multiple data sets. Work with User Experience designers and User Interface engineers as required to build front end applications. Present to and influences the team and business audience using the appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding. Customize communication style based on stakeholder under guidance and leverage rational arguments. Guide and mentor junior associates on story types, structures, and techniques based on context. Data Quality Management: Promote and educate others on data quality awareness. Profile, analyze, and assess data quality. Test and validate data quality requirements. Continuously measure and monitor data quality. Deliver against data quality service level agreements. Manage operational Data Quality Management procedures. Manage data quality issues and leads data cleansing activities to remove data quality defects, improve data quality, and eliminate unused data. Determine user accessibility and remove or restrict user access as needed. Interpret company and regulatory policies on data. Educate others on data governance processes, practices, policies, and guidelines. Exploratory Data Analysis: Collect and tabulate data and evaluate results to determine accuracy, validity, and applicability. Support the identification and application of statistical techniques based on requirements. Apply suitable technique under direction from leadership. Assist in the planning, design and implementation of exploratory data analysis research projects. Understand existing statistical models and identify and recommend statistical models based on hypothesis. Conduct statistical analysis and build basic statistical models using relevant packages/software suites. Data Strategy: Understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.
Requirements
- Bachelor's degree or the equivalent in Business, Engineering, Statistics, Economics, Analytics, Information Technology, or related field plus 2 years of experience in data analysis, data science, or related experience; OR 4 years of experience in data analysis, data science, or related experience.
- Must have experience with: Developing storytelling dashboards in Tableau Desktop and PBI and publishing them on a server which has connected with different data sources such as: Oracle (GRS/CKB), My SQL, Teradata, Prod 17, DB2 and GCP(BQ); Work on migration of Teradata Database to GCP and Hadoop system; Using Query IT, Hive tool to access Hadoop files; Blending data from multiple sources to discover new opportunities; Working to develop a front-end navigation scheme to support a formal dashboard portfolio strategy, including strategic, tactical, and operational dashboards; Migrating existing legacy reports into Tableau while building new reports from formal data warehouse initiative; Working to develop and manage the Tableau semantic layer through reusable data sources and KPIs helping client to see the trends in the sales data and forecast sales; Creating and extracting large data sets on sales and shared files to performing complex computations using Python to create a BQ tables and schedule refresh; Developing Spark code using Scala, Python and Spark SQL to fetch item and product related data from different data sources; Performance tuning of Targets, Sources, Mappings and Sessions; Performing real-time analysis of the incoming data using Kafka consumer API, Kafka topics, Spark Streaming utilizing Scala; PL/SQL programming - Stored Procedures, Functions, Packages, SQL tuning, and creation of Objects - Tables, Views, Materialized Views, Triggers, Sequences, Synonyms, etc.
- Employer will accept any amount of experience with the required skills.
Responsibilities
- Translate/co-own business problems within one's discipline to data related or mathematical solutions.
- Identify appropriate methods/tools to be leveraged to provide a solution for the problem.
- Share use cases and give examples to demonstrate how the method would solve the business problem.
- Provide recommendations to business stakeholders to solve complex business issues.
- Develop business cases for projects with a projected return on investment or cost savings.
- Translate business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact.
- Serve as interpreter and conduit to connect business needs with tangible solutions and results.
- Identify and recommend relevant business insights pertaining to their area of work.
- Provide and support the implementation of business solutions by building relationships and partnerships with key stakeholders; identify business needs; determine and carry out necessary processes and practices; monitor progress and results; recognize and capitalize on improvement opportunities; and adapt to competing demands, organizational changes, and new responsibilities.
- Support the understanding of the priority order of requirements and service level agreements.
- Help identify the most suitable source for data that is fit for purpose.
- Perform initial data quality checks on extracted data.
- Generate appropriate graphical representations of data and model outcomes.
- Understand customer requirements to design appropriate data representation for multiple data sets.
- Work with User Experience designers and User Interface engineers as required to build front end applications.
- Present to and influences the team and business audience using the appropriate data visualization frameworks and conveys clear messages through business and stakeholder understanding.
- Promote and educate others on data quality awareness.
- Profile, analyze, and assess data quality.
- Test and validate data quality requirements.
- Continuously measure and monitor data quality.
- Deliver against data quality service level agreements.
- Manage operational Data Quality Management procedures.
- Manage data quality issues and leads data cleansing activities to remove data quality defects, improve data quality, and eliminate unused data.
- Determine user accessibility and remove or restrict user access as needed.
- Interpret company and regulatory policies on data.
- Educate others on data governance processes, practices, policies, and guidelines.
- Collect and tabulate data and evaluate results to determine accuracy, validity, and applicability.
- Support the identification and application of statistical techniques based on requirements.
- Apply suitable technique under direction from leadership.
- Assist in the planning, design and implementation of exploratory data analysis research projects.
- Understand existing statistical models and identify and recommend statistical models based on hypothesis.
- Conduct statistical analysis and build basic statistical models using relevant packages/software suites.
- Understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
1-10 employees
