Principal Data Engineer

What you'll do...

Position: Principal Data Engineer

Job Location: 300 Elliott Avenue W., Seattle, WA 98119

Duties: Understands the priority order of requirements and service level agreements. Defines and identifies the most suitable sources for required data that is fit for purpose, referring to external sources as required. Performs initial data quality checks on the extracted data. Reviews the deliverables of junior associates and provides guidance on data source and quality. Builds the infrastructure required for optimal transformation and integration from a wide variety of data sources using appropriate data integration technologies. Uses modern tools, techniques, and architectures to partially or completely automate the most common, repeatable and tedious data preparation and integration tasks. Deploys pipelines using scheduling and orchestration frameworks. Evaluates impacts of data issues and risks at an early stage. Identifies needs and creates methods to fuse and reshape complex, multi-source data and make it usable for modeling. Updates knowledge of current and emerging big data analytics and data science trends and techniques. Assembles large, complex data across all data platforms (for example, relational, dimensional, NoSQL) and data tools. Builds complex logical and conceptual models and provides guidance to team on physical data models. Identifies and defines the appropriate techniques for exposing data toother systems. Reviews and provides guidance and inputs on all data modeling activities to team members. Creates and maintains critical data documentation and metadata that allows data to be understood and leveraged as a shared asset. Assists in defining data modeling standards and foundational best practices. Provides inputs to the architectural design to make best use of the available resources, given goals, and expected loads. Reviews the solution and application design to ensure it meets business, technical, and data requirements. Identifies language and libraries to use in the development process. Maps test cases to business and functional requirements. Creates proof of concepts. Reviews and troubleshoots code in line with final designs. Identifies and recommends the appropriate testing methodology. Identifies the environment(s) for deployment. Identifies and recommends modifications of application based on different environment requirements. Identifies modifications needed for scalability and drives the change. Monitors applications in production and leads development of patches where required. Reviews and ensures all code documentation is complete and updated periodically. Analyzes the business problem within one's discipline and questions assumptions to help the business identify the root cause. Identifies and recommends approach to resolve the business problem to create effective technology focused solutions. Sets relevant deliverables based on the established success criteria and define key metrics to measure progress and effectiveness of the solution. Quantifies business impact.

Minimum education and experience required: Bachelor’s degree or the equivalent in Computer Science, Software Engineering or related field and 5 years of post-bachelor’s progressively responsible experience in software engineering, data engineering, database engineering, business intelligence, business analytics or related field; OR Master's degree or the equivalent in Computer Science, Software Engineering or related field and 3 years of experience in software engineering, data engineering, database engineering, business intelligence, business analytics or related field.

Skills required: Experience designing and implementing data pipelines using Apache Spark and PySpark. Experience building and maintaining data lakes using AWS. Experience developing ETL workflows using Apache Airflow. Experience writing complex SQL queries and performance tuning. Experience implementing data modeling and data warehousing solutions (Snowflake and Databricks). Experience programming in Python for data engineering tasks. Experience using CI/CD tools (GitHub Actions and Terraform) for data pipeline deployment. Experience monitoring, and alerting data quality and issues across Data warehouse with tools like Monte Carlo and AWS CloudWatch. Experience performing cost optimization and resource tagging for data lake infrastructure. Experience mentoring junior engineers and conducting code reviews. Experience leading data architecture design and strategy across teams. Employer will accept any amount of experience with the required skills.

Salary Range: $178,069/year to $312,000/year. Additional compensation includes annual or quarterly performance 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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