Walmart Part Time Jobs From Home $25An Hour - WFH Id-3463
Do you have a passion for data and enjoy pushing the boundaries of innovation? Do you thrive in solving complex challenges while driving impactful results? If so, we have the perfect opportunity for you.
As a Data Engineer III in the Marketplace Strategy and Analytics team at Walmart eCommerce, you'll play a critical role in developing cutting-edge data engineering solutions that fuel our marketplace's growth. Working with vast datasets, you'll create scalable and efficient data pipelines, collaborate with Data Scientists and Analysts, and transform raw data into valuable, actionable insights. If you're eager to use your skills to shape the future of eCommerce and contribute to our mission of helping customers live better, read on.
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Key Responsibilities
- Data Engineering & Analytics: Design and implement data engineering solutions using Big Data platforms like Spark, Hadoop, and BigQuery to support real-time data streaming and processing.
- Data Transformation: Build data pipelines and orchestrate data workflows that convert raw data into high-quality, consumable datasets for Data Scientists and Analysts.
- Collaboration: Partner with Data Scientists, Analysts, engineers, and business stakeholders to solve complex business problems and enhance marketplace capabilities.
- Problem-Solving: Use analytics, automation, and big data solutions to formulate and solve business challenges within your discipline.
- Data Governance: Assist in defining and maintaining data governance processes to ensure data quality, consistency, and security.
- Data Strategy & Modeling: Contribute to the development of data strategy and architectural models (logical, physical) that align with business needs.
- Code Development & Testing: Write and test code in SQL, Java, Python, and/or Scala, ensuring quality standards and scalability for production environments.
- Mentorship: Guide junior engineers and help troubleshoot and resolve issues in data systems.
Required Qualifications
- 3+ years of experience in data engineering, analytics, and working with Big Data platforms (e.g., Spark, Hadoop, BigQuery).
- Hands-on experience creating real-time data streaming and processing with tools like Kafka and Spark Streaming.
- Proficient in writing complex and highly optimized SQL queries and leveraging programming languages such as Java, Python, and Scala.
- Expertise in building and managing data pipelines using Apache Airflow.
- Experience with public cloud platforms such as Google Cloud or Azure.
- Familiarity with distributed SQL query engines like Presto.
- Strong understanding of relational databases (SQL Server, MySQL, Oracle, etc.) and data modeling concepts.
Preferred Qualifications
- Experience in developing data solutions at scale, including data governance, data integration, and data transformation.
- Ability to apply business acumen to solve complex problems and support business case development.
- Familiarity with data science trends and a willingness to stay updated with the latest technologies.
Benefits & Perks
At Walmart, we believe in supporting our associates both professionally and personally. Enjoy a wide range of benefits including:
- Competitive pay with performance-based incentives
- 401(k) matching and stock purchase plans
- Paid maternity and parental leave
- Generous Paid Time Off (PTO) and multiple health plan options
- Career growth opportunities and professional development support
Why Walmart?
Walmart is not only the world’s largest retailer but also a company that prioritizes inclusivity, diversity, and community impact. Join a team that is shaping the future of shopping with cutting-edge technology while fostering an environment that encourages creativity, innovation, and kindness.
Whether you’re working remotely or from our offices, you’ll be part of a collaborative and supportive culture. With the scale of a Fortune 1 company and the energy of a startup, you’ll have the opportunity to drive change and make a real difference in the lives of millions of customers every week.