Senior, Data Engineer
Walmart · Bengaluru · Posted 2026-07-21
Tech stack: Google Cloud, SQL
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About the role
The team is dedicated to developing and maintaining a centralized, scalable, and secure data platform that integrates customer and store data from multiple organizational sources. This platform supports data-driven decision-making, advanced analytics, and tailored customer experiences. The team also ensures strong privacy practices, policies, and technologies to protect personal information throughout its lifecycle. By enabling reliable data access and safeguarding sensitive information, the team plays a vital role in fostering trust with suppliers and merchants while driving impactful business insights and operational excellence.
Responsibilities:
- Translate complex business problems into data-driven solutions by leveraging advanced analytics and big data techniques.
- Design, develop, and maintain scalable data pipelines and architectures using cloud platforms such as Google Cloud Platform and tools like Spark and Airflow.
- Perform data modeling, transformation, and integration to support business insights and decision-making processes.
- Optimize query performance and ensure data quality through rigorous testing and validation.
- Collaborate with stakeholders to align data engineering efforts with business strategy and requirements.
- Implement data governance practices to maintain compliance with regulatory standards.
- Continuously evaluate emerging technologies to enhance data processing capabilities.
Qualifications:
- Extensive experience in data engineering, including designing and developing scalable data pipelines and architectures.
- Proficiency with Big Data technologies such as Spark Core, PySpark, and Google Cloud Platform services including BigQuery and Dataproc.
- Strong SQL programming skills and expertise in query optimization for efficient data processing.
- Knowledge of data modeling techniques and tools to create logical and physical data models.
- Familiarity with CI/CD processes and workflow orchestration tools like Airflow.
- Ability to translate complex business requirements into technical solutions aligned with strategic goals.
Qualifications
- Extensive experience in data engineering, including designing and developing scalable data pipelines and architectures.
- Proficiency with Big Data technologies such as Spark Core, PySpark, and Google Cloud Platform services including BigQuery and Dataproc.
- Strong SQL programming skills and expertise in query optimization for efficient data processing.
- Knowledge of data modeling techniques and tools to create logical and physical data models.
- Familiarity with CI/CD processes and workflow orchestration tools like Airflow.
- Ability to translate complex business requirements into technical solutions aligned with strategic goals.
Responsibilities
- Translate complex business problems into data-driven solutions by leveraging advanced analytics and big data techniques.
- Design, develop, and maintain scalable data pipelines and architectures using cloud platforms such as Google Cloud Platform and tools like Spark and Airflow.
- Perform data modeling, transformation, and integration to support business insights and decision-making processes.
- Optimize query performance and ensure data quality through rigorous testing and validation.
- Collaborate with stakeholders to align data engineering efforts with business strategy and requirements.
- Implement data governance practices to maintain compliance with regulatory standards.
- Continuously evaluate emerging technologies to enhance data processing capabilities.