Senior Data Engineer

What you'll do...

Position: Senior Data Engineer

Job Location: 111 S Main St., Bentonville, AR 72712

Duties: 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 etc; understanding of the methods and applications that unlock the monetary value of data assets. To understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function. 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. To 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 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; techniques such as decision trees, advanced regression techniques such as LASSO methods, random forests etc; 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. Tech. problem formulation including analytics/big data analytics/automation techniques and methods; business understanding; Precedence and use cases; Business requirements and insights. To 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 including industry and environmental factors; common business vernacular; business practices across two or more domains such as product, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; directly relevant business metrics and business areas. To 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.

Minimum education and experience required: Master’s degree or the equivalent in Computer Science, Information Technology, Engineering, or 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, or related field plus 3 years of experience in software engineering or related experience.

Skills required: Must have experience with: designing and implementing highly scalable, optimized, distributed big data pipelines and ETLs using frameworks like Hadoop, Hive, Spark, and Databricks; following industry standard coding, design, and development practices to implement data pipelines using object-oriented programming languages like Scala, Python, and Java; cloud platforms and services like Microsoft Azure, Google Cloud Platform (GCP), Databricks, and Snowflake for implementations; orchestrating and automating implemented pipeline solutions using tools and frameworks like Automic, Autosys, Oozie, and Apache Airflow; writing efficient SQLs for data querying from RDBMS and data warehousing frameworks like Apache Hive and Snowflake; setting up CI/CD processes by leveraging tools like Maven, Gradle, Jenkins, Looper, JFrog, and Artifactory; data modelling of tables created on systems like RDBMS, Apache Hive, and Snowflake for better consumption; leading new efforts, mentoring team of engineers, communicating complex technical solutions and ideas to both technical and non-technical team members, and implementing ideas take to the production scale; using shell scripting to automate and streamline manual processes and building small ETLs and frameworks; using version control systems like Git and GitHub for collaborative code management, tracking changes, code review, and ensuring effective teamwork and codebase integrity; and designing and building data lakes, architecture of distributed systems, and distributed computing solutions. Employer will accept any amount of experience with the required skills.

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Wal-Mart is an Equal Opportunity Employer.