Software Engineer III
Walmart · Bengaluru · 3+ yrs experience · Posted 2026-07-23
Tech stack: Azure, GCP, Google Cloud, Java, Jenkins, Kafka, SQL
Apply on the company site · Get a referral for this role
Walmart salary & ratings · Walmart interview process · More live openings
About the role
Omni Services - Creating Frictionless End to End Omni channel Customer Journey – Store experience, Digital App, Data insights to power Smooth retail shopping and check out experience to make our customers smile and our developers proud! The Omni Services at IDC owns several areas of the Store Services in Digital Retail like Wireless, BPO, SIM and ACC. We are responsible for architecture, design and delivery of programs within the areas we own. We work on Backend Technologies hosted on premises, Cloud Hosted and Applications across Web, Android and IOS for Walmart US markets. This eco system uses Core java Technologies, Azure Cloud Technology.
Responsibilities:
- As a Data Engineer, you will play a critical role in designing, developing, and implementing data pipelines and data integration solutions using Google Cloud Platform (GCP) and SQL Server.
- You will be responsible for building scalable and efficient data processing systems, optimizing data workflows, and ensuring data quality and integrity.
- Monitor and troubleshoot data pipelines to ensure data availability and reliability
- Conduct performance tuning and optimization of data processing systems for improved efficiency and scalability
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Work closely with data scientists and analysts to provide them with the necessary data sets and tools for analysis and reporting
- Create data tools for analytics team members that assist them in building and optimizing our product into an innovative industry leader.
- Stay up-to-date with the latest industry trends and technologies in data engineering and apply them to enhance the data infrastructure
- What You’ll bring Proven working experience as a Data Engineer with a minimum of 3+ years in the field.
- Familiarity with Google Cloud Platform (GCP) services such as BigQuery, GCS, Dataproc etc.
- Experience of developing near real-time ingestion pipelines using kafka and spark structured streaming.
- Experience with Data modelling, Data warehousing and ETL processes Understanding of data warehousing concepts and best practices Strong knowledge of SQL and NoSQL systems Proficiency in version control systems, particularly Git.
- Proficiency in working with large-scale data sets and distributed computing frameworks Familiarity with CI/CD pipelines and tools such as Jenkins.
- Proficiency with schedulers like Airflow.
- Strong problem-solving and analytical skills Familiarity with BI and Visualisation tools like PowerBI, Tableau or Looker
Qualifications:
- What You’ll bring Proven working experience as a Data Engineer with a minimum of 3+ years in the field.
- Familiarity with Google Cloud Platform (GCP) services such as BigQuery, GCS, Dataproc etc.
- Experience of developing near real-time ingestion pipelines using kafka and spark structured streaming.
- Experience with Data modelling, Data warehousing and ETL processes Understanding of data warehousing concepts and best practices Strong knowledge of SQL and NoSQL systems Proficiency in version control systems, particularly Git.
- Proficiency in working with large-scale data sets and distributed computing frameworks Familiarity with CI/CD pipelines and tools such as Jenkins.
- Proficiency with schedulers like Airflow.
- Strong problem-solving and analytical skills Familiarity with BI and Visualisation tools like PowerBI, Tableau or Looker
Qualifications
- What You’ll bring Proven working experience as a Data Engineer with a minimum of 3+ years in the field.
- Familiarity with Google Cloud Platform (GCP) services such as BigQuery, GCS, Dataproc etc.
- Experience of developing near real-time ingestion pipelines using kafka and spark structured streaming.
- Experience with Data modelling, Data warehousing and ETL processes
- Understanding of data warehousing concepts and best practices
- Strong knowledge of SQL and NoSQL systems
- Proficiency in version control systems, particularly Git.
- Proficiency in working with large-scale data sets and distributed computing frameworks
- Familiarity with CI/CD pipelines and tools such as Jenkins.
- Proficiency with schedulers like Airflow.
- Strong problem-solving and analytical skills
- Familiarity with BI and Visualisation tools like PowerBI, Tableau or Looker
Responsibilities
- As a Data Engineer, you will play a critical role in designing, developing, and implementing data pipelines and data integration solutions using Google Cloud Platform (GCP) and SQL Server.
- You will be responsible for building scalable and efficient data processing systems, optimizing data workflows, and ensuring data quality and integrity.
- Monitor and troubleshoot data pipelines to ensure data availability and reliability
- Conduct performance tuning and optimization of data processing systems for improved efficiency and scalability
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Work closely with data scientists and analysts to provide them with the necessary data sets and tools for analysis and reporting
- Create data tools for analytics team members that assist them in building and optimizing our product into an innovative industry leader.
- Stay up-to-date with the latest industry trends and technologies in data engineering and apply them to enhance the data infrastructure
- What You’ll bring Proven working experience as a Data Engineer with a minimum of 3+ years in the field.
- Familiarity with Google Cloud Platform (GCP) services such as BigQuery, GCS, Dataproc etc.
- Experience of developing near real-time ingestion pipelines using kafka and spark structured streaming.
- Experience with Data modelling, Data warehousing and ETL processes
- Understanding of data warehousing concepts and best practices
- Strong knowledge of SQL and NoSQL systems
- Proficiency in version control systems, particularly Git.
- Proficiency in working with large-scale data sets and distributed computing frameworks
- Familiarity with CI/CD pipelines and tools such as Jenkins.
- Proficiency with schedulers like Airflow.
- Strong problem-solving and analytical skills
- Familiarity with BI and Visualisation tools like PowerBI, Tableau or Looker