Position: Principal Data Engineer

Job Location: 850 Cherry Avenue, San Bruno, CA 94066

Duties: Translates business problems to data related solutions. Uses big data analytics and automation, and provides solutions for business use cases. Translates business requirements into projects, activities, tasks, and connect business needs with solutions and results and recommends new processes. Works on identifying suitable data sources for reporting ask. Explores data and finds how can it be used. Analyzes data for quality checks. Develops the Logical Data Model and Physical Data Models along with data warehouse and data mart designs. Analyzes complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Analyzes data-related system integration challenges and proposes appropriate solutions. Oversees the tasks of less experienced programmers. Explores internal and external data sources to understand its data collection process, storage location and what is relation among them. Utilizes ETL batch processing, streaming ingestion, REST API for data transformation and integration. Creates data pipelines for processing structured and semi-structured data in Data warehouse and Data Mart. Uses MPP (Massively parallel processing) databases Teradata, Presto or Google BigQuery for data exploration and analysis. Works with BI and data science team members to assist them in accessing and leveraging key data sets. Develops analytical data mart for marketing and customer reporting by designing and developing Hive and Spark ETL data pipelines and leveraging Sales, Marketing and Clickstream datasets. Works with User Interface engineers as required to build front end applications for reporting. Understands customer requirements to design appropriate data representation for multiple data sets. Uses Data Discovery tools to analyze data residing in different data sources to identify patterns, trends, outliers, and correlations. Explores the data to determine accuracy, validity, and applicability. Assists in the planning, design, and implementation of data analysis projects. For Data Integrity and Data Quality, measures and monitors the data quality by testing and validating data. Manages data quality issues, cleanses data for fixing defect and removes unused data. For user’s accessibility of data, removes or restricts user access as needed. Develops data pipelines for the required solution and application features by leveraging business, technical, and data requirements. Creates proofs of concept. Contributes to code documentation, maintains playbooks. Understands and complies and guides others with company data governance processes along with regulatory requirements around data privacy, security, storage, retention, and documentation. Provides expert advice and guidance to others in the application of information and best practices.  Manages a team of engineering resources, sets priorities, establishes vision, improvises solutions for technical challenges, closely partners with the tech product and works in agile fashion. 1 direct report: Senior Data Engineer.

Minimum education and experience required: Bachelor’s degree or equivalent in Computer Science, Software Engineering, Information Technology or related field and 5 years of experience in data engineering, database engineering, business intelligence, or business analytics or related field; OR Master's degree or equivalent in Computer Science, Software Engineering, Information Technology or related field and 3 years of experience in data engineering, database engineering, business intelligence, or business analytics or related field.

Skills required: Experience with big data tools including Apache Spark, Spark SQL, Hive, HDFS, and Airflow. Experience with Cloud Technologies including Google Cloud Platform service such as Compute Engines, DataProc, PubSub, BigQuery, and Composure. Experience in Relational SQL and NoSQL databases including Cloud SQL, PostgreSQL, and Cassandra. Experience in Object Oriented Programming using Python and Scala. Experience in Linux shell scripting. Experience in Data Warehouse and Data Lake. Experience designing and implementing REST API for exposing data to applications. Experience in MPP (Massively parallel processing) databases Teradata, Presto, and Google BigQuery for data exploration and analysis. Experience building data pipeline for ETL and ELT batch processing, streaming ingestion, REST API for data transformation and integration. Experience processing structured and semi-structured data. Experience in performance Tuning of Hive and Spark jobs. Experience in Data Modeling. Experience in Sales, Marketing, and Clickstream datasets. Experience in data migration.  Employer will accept any amount of experience with the required skills.

Salary Range: $188,885/year to $286,000/year. Additional compensation includes annual or quarterly performance incentives.  Additional compensation for certain positions may also include: Regional Pay Zone (RPZ) (based on location) and Stock equity incentives.

Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.com.

Wal-Mart is an Equal Opportunity Employer.

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