Senior Data Enginner

Walmart • Bentonville, AR

15h

About The Position

This notice is being provided as a result of the filing of an Application for Permanent Alien Labor Certification. Any person may provide documentary evidence bearing on the application to the Certifying Officer of the Department of Labor: U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue, NW, Room N-5311, Washington, DC 20210 What you'll do... Job title: Senior Data Enginner Work address: 1 Customer Drive, Bentonville AR 72716 Duties: Data Strategy: understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function. Data Source Identification: support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data. Data Transformation and Integration: extract data from identified databases. Creates data pipelines and transform data to a structure that is relevant to the problem by selecting appropriate techniques. Develops knowledge of current data science and analytics trends. Tech. Problem Formulation: translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem. Understanding Business Context: provide recommendations to business stakeholders to solve complex business issues. Develops business cases s for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Data Modeling: analyze complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Develops the Logical Data Model and Physical Data Models including data warehouse and data mart designs. Defines relational tables, primary and foreign keys, and stored procedures to create a data model structure. Evaluates existing data models and physical databases for variances and discrepancies. Develops efficient data flows. Analyzes data-related system integration challenges and proposes appropriate solutions. Creates training documentation and trains end-users on data modeling. Oversees the tasks of less experienced programmers and stipulates system troubleshooting supports. Code Development and Testing: write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Creates test cases to review and validate the proposed solution design. Creates proofs of concept. Tests the code using the appropriate testing approach. Deploys software to production servers. Contributes code documentation, maintains playbooks, and provides timely progress updates. Data Governance: establish, modify, and document data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines. Provides recommendations on needed updates or inputs into data governance policies, practices or guidelines.

Requirements

• implementing ETL Pipelines and creating data movement solutions from legacy sources using Spark with Scala or Python
• building batch and Real Time Data Pipelines ingesting with Kafka and processing using Spark streaming or Structured streaming
• a variety of data sources for data extraction and efficient storage using databases like SQL Server, Oracle, and Teradata
• data analysis with the help of query languages like SQL, Spark SQL and Hive to extract insights by translating raw data into meaningful data that contributes in data driven decision making
• developing Adhoc, summary reports and visualizations to identify key trends in data (Tableau, Excel)
• implementing CI/CD Pipelines using Jenkins and using GIT for source control management
• developing and deploying applications working with cloud technologies Amazon Web Services, Google Cloud or Microsoft Azure
• Release management tools including JIRA and Wiki
• Scripting in Unix Shell
• Process scheduling & monitoring tools including Airflow or SAP BW
• Coding in an Object-oriented programming language like Scala or Python
• designing Snowflake and Star Schema Data Models to support Business Intelligence Applications
• Master’s degree or the equivalent in Computer Science, Information Technology, Engineering, Business Analytics or a related field plus 1 year of experience in software engineering or related experience OR Bachelor's degree or the equivalent in Computer Science, Information Technology, Engineering, Business Analytics or a related field plus 3 years of experience in software engineering or related experience

Responsibilities

• Data Strategy: understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function.
• Data Source Identification: support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data.
• Data Transformation and Integration: extract data from identified databases. Creates data pipelines and transform data to a structure that is relevant to the problem by selecting appropriate techniques. Develops knowledge of current data science and analytics trends.
• Tech. Problem Formulation: translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem.
• Understanding Business Context: provide recommendations to business stakeholders to solve complex business issues. Develops business cases s for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work.
• Data Modeling: analyze complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Develops the Logical Data Model and Physical Data Models including data warehouse and data mart designs. Defines relational tables, primary and foreign keys, and stored procedures to create a data model structure. Evaluates existing data models and physical databases for variances and discrepancies. Develops efficient data flows. Analyzes data-related system integration challenges and proposes appropriate solutions. Creates training documentation and trains end-users on data modeling. Oversees the tasks of less experienced programmers and stipulates system troubleshooting supports.
• Code Development and Testing: write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Creates test cases to review and validate the proposed solution design. Creates proofs of concept. Tests the code using the appropriate testing approach. Deploys software to production servers. Contributes code documentation, maintains playbooks, and provides timely progress updates.
• Data Governance: establish, modify, and document data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines. Provides recommendations on needed updates or inputs into data governance policies, practices or guidelines.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level