What you'll do...

Position: Data Engineer III

Job Location: 702 SW 8th St., Bentonville, AR 72716

Duties: Performs data governance including data value chains; data processes and practices; regulatory and ethical requirements around data; data modeling, storage, integration, and warehousing; data value chains (identification, ingestion, processing, storage, analysis, and utilization); data quality framework and metrics; regulatory and ethical requirements around data privacy, security, storage, retention, and documentation; business implications on data usage; data strategy; enterprise regulatory and ethical policies and strategies. Supports the documentation of data governance processes. Supports the implementation of data governance practices. Conduct Data Strategy including understanding of business value and relevance of data and data enabled insights/decisions; appropriate application and understanding of data ecosystem including data management, data quality standards and data governance, accessibility, storage and scalability. Understands methods and applications that unlock the monetary value of data assets. Understands, articulates, and applies principles of defined strategy to routine business problems that involve a single function. Perform data source identification including functional business domain and scenarios; categories of data and where it is held; business data requirements; database technologies and distributed datastores (e.g. SQL, NoSQL); data quality; existing business systems and processes, including the key drivers and measures of success. Supports understanding of 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. Conducts data transformation and integration including internal and external data sources including how they are collected, where and how they are stored, and interrelationships, both within and external to the organization; techniques like ETL batch processing, streaming ingestion, scrapers, API and crawlers; data warehousing service for structured and semi-structured data, or to MPP databases such as Snowflake, Microsoft Azure, Presto or Google BigQuery; Pre-processing techniques such as transformation, integration, normalization, feature extraction, to identify and apply appropriate methods. Utilizes techniques such as decision trees, advanced regression techniques such as LASSO methods, and random forests, cloud, and big data environments like EDO2 systems to 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. Conducts data modeling, including cloud data strategy, data warehouse, data lake, and enterprise big data platforms; data modeling techniques and tools (For example, Dimensional design and scalability), Entity Relationship diagrams, and Erwin; Query languages SQL / NoSQL; Data flows through the different systems; tools supporting automated data loads; Artificial Intelligent - enabled metadata management tools and techniques. Analyzes complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Develops 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.

Minimum education and experience required: Master's degree or the equivalent in Computer Science, Information Technology, Engineering, or related field; OR Bachelor's degree or the equivalent in Computer Science, Information Technology, Engineering, or related field plus 2 years of experience in software engineering or a related field.

Skills required: Must have experience with: Creating automated frameworks using Python; Designing and Developing ETL workflows by leveraging Spark and Databricks frameworks; Implementing CI/CD pipelines using Jenkins and Git for source control management; Practicing Agile Methodology for software development; Orchestrating the ETL Jobs by using Airflow Dags; Writing SQL queries to query against RDBMS for data analysis and implementing business logics in ETL workflows; Creating and presenting dashboards on data and to business users; Data processing, analysis and storing used Snowflake; Creating data lakes in Azure Blob and AWS s3 storage by ingesting from different sources and creating Hive tables; Ingesting data into on-prem Oracle database using Informatica; Creating and managing clusters in EMR to run spark jobs. Employer will accept any amount of experience with the required skills.

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Wal-Mart is an Equal Opportunity Employer.