Senior Data Engineer
WeVision LLC
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Irvine, CA
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Mid-Senior level
Posted March 26, 2026
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Responsibilities
Commitments
Responsibilities
- Design, develop, and maintain large-scale data pipelines that capture and process consumer interaction data across multiple platforms.
- Contribute to the development of the Audience Manager Platform (AMP), a centralized system that unifies customer profiles and provides a trusted source of audience insights.
- Build scalable and fault-tolerant data processing systems to ensure reliable delivery of audience data to multiple business endpoints.
- Develop backend data services and pipelines that support data ingestion, transformation, and activation workflows.
- Work with cross-functional teams including data scientists, analytics teams, product teams, and business stakeholders to enable timely access to high-quality audience data.
- Optimize and maintain distributed data processing frameworks to improve system performance and scalability.
- Ensure high data quality, reliability, and observability across production data systems.
- Serve as a technical point of contact or SME for data engineering systems in a multi-system production environment.
Commitments
Location Preference
Candidates based in California are strongly preferred.
Not Met Priorities
What still needs stronger evidence
Requirements
- 4+ years of experience in big data engineering, building and maintaining large-scale data pipelines.
- Hands-on experience with distributed data processing systems such as Spark (PySpark) or Flink.
- Strong programming skills in Python and SQL for processing large datasets.
- Experience with at least one MPP or cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks.
- Solid understanding of data modeling, data warehousing concepts, and best practices.
- Experience supporting production data environments and acting as a technical point of contact or subject matter expert.
- Strong analytical, problem-solving, and communication skills, with high attention to detail.
- Minimum of 4 years of relevant professional experience in data engineering or related roles.
Preferred Skills
- Experience working with AWS cloud technologies (e.g., S3, ECS, EMR, EC2, Lambda).
- Hands-on experience with data orchestration and integration tools such as Airflow.
- Familiarity with CI/CD practices for data pipelines.
- Experience working within Agile or Scrum development environments.
- Candidates based in California are strongly preferred.
Education
- (Not required) – Education
- (Not required) – Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Electrical/Electronics Engineering, or a related technical field, or equivalent practical experience.
- (Required) – Minimum of 4 years of relevant professional experience in data engineering or related roles.
About the Role We are seeking a Sr. Data Engineer Consultant to support the development and enhancement of a large-scale Audience Data Platform (AMP) for a leading global streaming and media technology company. This platform serves as the centralized audience data hub, capturing and processing consumer behavior across multiple channels and delivering summarized insights to downstream systems that support marketing, analytics, product, and business decision-making. As a Sr.Data Engineer Consultant, you will play a key role in building scalable and reliable data infrastructure that enables the organization to maintain a comprehensive and trusted source of customer data. Your work will directly impact how teams across the company understand audiences, generate insights, and activate data-driven strategies. What You Will Do
Design, develop, and maintain large-scale data pipelines that capture and process consumer interaction data across multiple platforms.
Contribute to the development of the Audience Manager Platform (AMP), a centralized system that unifies customer profiles and provides a trusted source of audience insights.
Build scalable and fault-tolerant data processing systems to ensure reliable delivery of audience data to multiple business endpoints.
Develop backend data services and pipelines that support data ingestion, transformation, and activation workflows.
Work with cross-functional teams including data scientists, analytics teams, product teams, and business stakeholders to enable timely access to high-quality audience data.
Optimize and maintain distributed data processing frameworks to improve system performance and scalability.
Ensure high data quality, reliability, and observability across production data systems.
Serve as a technical point of contact or SME for data engineering systems in a multi-system production environment. Basic Qualifications
4+ years of experience in big data engineering, building and maintaining large-scale data pipelines.
Hands-on experience with distributed data processing systems such as Spark (PySpark) or Flink.
Strong programming skills in Python and SQL for processing large datasets.
Experience with at least one MPP or cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks.
Solid understanding of data modeling, data warehousing concepts, and best practices.
Experience supporting production data environments and acting as a technical point of contact or subject matter expert.
Strong analytical, problem-solving, and communication skills, with high attention to detail. Preferred Qualifications
Experience working with AWS cloud technologies (e.g., S3, ECS, EMR, EC2, Lambda).
Hands-on experience with data orchestration and integration tools such as Airflow.
Familiarity with CI/CD practices for data pipelines.
Experience working within Agile or Scrum development environments. Education
Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Electrical/Electronics Engineering, or a related technical field, or equivalent practical experience.
Minimum of 4 years of relevant professional experience in data engineering or related roles. Location Preference
Candidates based in California are strongly preferred.
Design, develop, and maintain large-scale data pipelines that capture and process consumer interaction data across multiple platforms.
Contribute to the development of the Audience Manager Platform (AMP), a centralized system that unifies customer profiles and provides a trusted source of audience insights.
Build scalable and fault-tolerant data processing systems to ensure reliable delivery of audience data to multiple business endpoints.
Develop backend data services and pipelines that support data ingestion, transformation, and activation workflows.
Work with cross-functional teams including data scientists, analytics teams, product teams, and business stakeholders to enable timely access to high-quality audience data.
Optimize and maintain distributed data processing frameworks to improve system performance and scalability.
Ensure high data quality, reliability, and observability across production data systems.
Serve as a technical point of contact or SME for data engineering systems in a multi-system production environment. Basic Qualifications
4+ years of experience in big data engineering, building and maintaining large-scale data pipelines.
Hands-on experience with distributed data processing systems such as Spark (PySpark) or Flink.
Strong programming skills in Python and SQL for processing large datasets.
Experience with at least one MPP or cloud data warehouse such as Snowflake, Redshift, BigQuery, or Databricks.
Solid understanding of data modeling, data warehousing concepts, and best practices.
Experience supporting production data environments and acting as a technical point of contact or subject matter expert.
Strong analytical, problem-solving, and communication skills, with high attention to detail. Preferred Qualifications
Experience working with AWS cloud technologies (e.g., S3, ECS, EMR, EC2, Lambda).
Hands-on experience with data orchestration and integration tools such as Airflow.
Familiarity with CI/CD practices for data pipelines.
Experience working within Agile or Scrum development environments. Education
Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Electrical/Electronics Engineering, or a related technical field, or equivalent practical experience.
Minimum of 4 years of relevant professional experience in data engineering or related roles. Location Preference
Candidates based in California are strongly preferred.