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# Senior Data Engineer

- **Company:** Wal-Mart Stores, Inc.
- **Location:** Sunnyvale, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $144,402.0 - $234,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Database, Data Architecture, Information Engineering, Data Integrity, Extract Transform Load (ETL), Data Mart, Data Visualization, Data Flow Control, Apache Hive, Python (Programming Language), Parsing, Software Engineering, SQL Stored Procedures, SQL Databases, Data Streaming, Tableau (Software), Unstructured Data, Data Processing, Freeform SQL, Google Cloud, Snowflake, Apache Spark, Pyspark, Information Technology, Data Analytics, Google Bigquery, Looker Analytics, Data Pipelines
- **Published:** September 26, 2026
- **Apply:** https://www.jofdav.com/jobs/59877251-senior-data-engineer

## About the Role

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

Skills required: Must have experience with: Designing and building scalable data pipelines and ETL workflows to support analytical data warehouses; Developing complex SQL queries, views, stored procedures, and user-defined functions in cloud databases including Google BigQuery; Optimizing long-running queries and improving performance of large-scale analytical datasets; Parsing, cleansing, and transforming structured and unstructured data using Hive, Spark, and PySpark; Developing automation scripts and reusable tools using Python; Designing and implementing data models to support reporting, dashboarding, and self-service BI; Working with cloud platforms, including Google Cloud Platform (preferred), AWS, Azure, and Snowflake at scale; Leveraging cloud data pipeline orchestration tools: Airflow, Dataflow; Building analytical datasets to support Tableau and Looker; Performing data exploration and statistical analysis to uncover business insights and common data pitfalls; Identifying data
bottlenecks and implementing optimization strategies to enhance pipeline efficiency and data reliability; Producing technical documentation including data architecture diagrams, source-to-target mappings, and ETL workflow designs. Employer will accept any amount of experience with the required skills.

## Description

Duties: Designs and implements scalable data pipelines and automated reporting solutions to address business problems using analytics and big data technologies. Translates business requirements into analytical data models and actionable insights. Owns end-to-end delivery of data engineering tasks supporting business intelligence and self-service analytics initiatives. Builds and maintains ETL pipelines to transform raw data into analytics-ready datasets. Extracts, cleanses, and transforms structured and unstructured data using appropriate big data processing techniques such as Spark and Hive. Performs data exploration to identify trends, segmentation opportunities, funnel insights, and long-term business patterns. Develops and optimizes SQL queries to support reporting, dashboarding, and analytical use cases. Designs and maintains logical and physical data models for analytical data warehouses and data marts. Defines relational tables, primary and foreign keys, and transformation logic to
support scalable reporting structures. Evaluates and enhances data models and data flows to improve accuracy, reliability, and performance. Identifies bottlenecks in data processing pipelines and implements automation and optimization solutions to improve query performance and reporting efficiency. Performs data quality validation checks to ensure integrity and reliability of metrics. Develops reusable scripts and tools using Python and SQL to streamline data processing and reporting workflows. Partners with cross-functional stakeholders to enable self-service BI through structured datasets and dashboard-ready tables. Builds proof-of-concepts to evaluate emerging big data and data visualization technologies. Documents data architecture, data flows, and transformation logic to support analytics scalability and governance best practices. Stays current with big data, cloud analytics, and data visualization technology trends and makes recommendations based on business needs.