Senior Data Engineer

StartupNWA; Bentonville (AR); On-site; USD 90,000 - 180,000; Full time

Benefits offered by this job

Health benefits

401(k)

Stock purchase plan

Paid time off

Job summary

Walmart is seeking a Senior Data Engineer in Bentonville, AR to lead data engineering initiatives and guide a team of developers. The role involves building scalable data pipelines, applying data governance, and delivering data-enabled insights for business decisions.

You will work with cloud platforms, big data tools, and analytics to support enterprise data needs. The position offers competitive pay and comprehensive benefits in a fast-paced retail technology environment.

Qualifications

• Experience designing data pipelines and data models for large-scale environments.
• Proven ability to lead data engineering projects and mentor junior engineers.
• Strong knowledge of ETL/ELT, data warehousing, and data governance.

Responsibilities

• Oversees tasks of less experienced programmers and mentors team.
• Designs data strategy and data infrastructure to enable insights and decision making.
• Builds data pipelines from multiple sources and ensures data quality.

Skills

Apache Spark

Hadoop Ecosystem

Unix Shell Script

Apache Airflow

Oozie

Google Cloud Platform

Hive

Maven

Jenkins

Git

JIRA Scrum

Agile methodologies

Project Management

Education

Master's degree in Computer Science or related field

Bachelor's degree in Computer Science or related field

Tools

Snowflake

Microsoft Azure

Job description

What you'll do...

Position: Senior Data Engineer

Job Location: 811 Excellence Dr., Bentonville, AR 72716

Duties: Oversees the tasks of less experienced programmers and stipulates system troubleshooting supports. Utilizes data strategy, including understanding the business value and relevance of data and data-enabled insights and decisions; appropriate application and understanding of the data ecosystem, including data management, data quality standards, data governance, accessibility, storage, and scalability; and understanding the methods and applications that unlock the monetary value of data assets. Applies principles of the defined strategy to routine business problems that involve a single function. Utilizes data source identification, including functional business domains and scenarios, categories of data and where it is held, business data requirements, database technologies and distributed datastores such as SQL and NoSQL, data quality, and existing business systems and processes, including key drivers and measures of success. Supports the understanding of the priority order of requirements and service level agreements, helps identify the most suitable source for fit-for-purpose data, and performs initial data quality checks on extracted data. Utilizes data transformation and integration, including internal and external data sources, how data is collected, stored, and interrelated; techniques such as ETL batch processing, streaming ingestion, scrapers, APIs, and crawlers; data warehousing services for structured and semi-structured data or MPP databases such as Snowflake, Microsoft Azure, Presto, or Google BigQuery; preprocessing techniques such as transformation, integration, normalization, and feature extraction; analytical techniques such as decision trees, advanced regression techniques including LASSO methods, and random forests; and cloud and big data environments such as EDO2 systems. Extracts data from identified databases, creates data pipelines, transforms data into structures relevant to the problem using appropriate techniques, and develops knowledge of current data science and analytics trends. Utilizes technical problem formulation, including analytics, big data analytics, automation techniques and methods, business understanding, precedence and use cases, and business requirements and insights. Utilizes data modeling, including cloud data strategy, data warehouses, data lakes, and enterprise big data platforms; data modeling techniques and tools such as dimensional design, scalability, Entity Relationship diagrams, and Erwin; SQL and NoSQL query languages; data flows through different systems; tools supporting automated data loads; and AI-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 and physical data models including data warehouse and data mart designs; defines relational tables, primary and foreign keys, and stored procedures to create data model structures; 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; and oversees the tasks of less experienced programmers while stipulating system troubleshooting supports.

Minimum education and experience required: Master's degree or the equivalent in Computer Science or related field plus 1 year of experience in software engineering, data engineering, database engineering, business intelligence, business analytics or related field; or Bachelor's degree or the equivalent in Computer Science or related field plus 3 years of experience in software engineering, data engineering, database engineering, business intelligence, business analytics or related field.

Skills required: Must have experience with: Designed and implemented applications with Apache Spark; Frameworks used in Hadoop Ecosystem Components (Hadoop, HDFS, YARN, TEZ, MapReduce); Building Scripts using Unix Shell Script; Scheduled productions jobs using Apache Airflow and Oozie; Cloud Technologies (Google Cloud Platform) to execute the applications using clusters and data management; Writing Hive applications with HIVE query language; Deployment Tools (Maven and SBT); Implementing CI/CD pipelines using Jenkins and using Git for Source control management; Agile methodologies to follow up on day-to-day tasks in each sprint regards to story pointers (JIRA/Scrum); Project Management activities (initiation, planning, execution, monitoring and control, and closure); and Participated in requirements gathering from multiple teams for Project increment planning. Employer will accept any amount of experience with the required skills.

Rate of pay: $90,000.00 - 180,000.00/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.

Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.