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Data Exchange Jobs in California (NOW HIRING)

MSR Cosmos

AWS Data Architect

Torrance, CA · On-site

$66.50 - $85.50/hr

Data Exchange * Develop the required governance, security, monitoring and guard rails to enable efficient data exchange between internal application and their external vendors, partners, and SaaS ...

MSRCosmos

AWS Data Architect

Torrance, CA · On-site

$65.50 - $84.25/hr

Data Exchange * Develop the required governance, security, monitoring and guard rails to enable efficient data exchange between internal application and their external vendors, partners, and SaaS ...

CYNET SYSTEMS

Data Tech Lead with Java

Aliso Viejo, CA · On-site

$61 - $66/hr

Develop API automation and integration solutions for data exchange between enterprise systems. Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading ...

Office Ally

Senior Integration Engineer

Clayton, CA · Hybrid

Jopari delivers innovative solutions for electronic billing, payments, and secure data exchange across the Property & Casualty and Healthcare industries. As a Senior Integration Engineer, you will ...

Office Ally

Senior Integration Engineer

Concord, CA · Hybrid

Jopari delivers innovative solutions for electronic billing, payments, and secure data exchange across the Property & Casualty and Healthcare industries. As a Senior Integration Engineer, you will ...

Office Ally

Senior Integration Engineer

Berkeley, CA · Hybrid

Jopari delivers innovative solutions for electronic billing, payments, and secure data exchange across the Property & Casualty and Healthcare industries. As a Senior Integration Engineer, you will ...

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Data Exchange information

Is 40 too late for data science?

Data exchange roles often require strong analytical skills and familiarity with data management tools. Age is generally not a barrier; many professionals successfully transition into data science or related fields at age 40 or later by gaining relevant skills through courses, certifications, and practical experience.

What are the typical daily responsibilities of someone working in a Data Exchange role?

Professionals in Data Exchange roles are responsible for managing the secure transfer of data between different systems or organizations. This often includes monitoring data exchange processes, troubleshooting data flow issues, maintaining data integrity, and ensuring compliance with data privacy standards. You may also collaborate closely with IT, data analytics, and compliance teams to define requirements and support new integration projects. Daily tasks typically involve working with various data formats, updating documentation, and responding to any data-related incidents or requests. The role is dynamic and fast-paced, offering an engaging environment for those who enjoy working at the intersection of technology and business operations.

What is the highest paying data job?

The highest paying data jobs typically include Data Science Directors, Chief Data Officers, and Data Engineering Managers, with salaries often exceeding $150,000 annually. These roles require advanced skills in data analysis, machine learning, and leadership, and often demand extensive experience and relevant certifications.

What does data exchange do?

A Data Exchange professional manages the transfer and sharing of data between systems, organizations, or platforms to ensure accurate, secure, and efficient data flow. They often work with data integration tools, follow data governance standards, and troubleshoot data transfer issues to support business operations and decision-making.

What are the key skills and qualifications needed to thrive in the Data Exchange position, and why are they important?

To thrive in a Data Exchange role, you need a strong background in data management, data integration, and knowledge of standards such as HL7, EDI, or API protocols, typically supported by a degree in information systems or computer science. Experience with data exchange platforms, ETL tools (such as Informatica or Talend), and familiarity with data security best practices is often required. Excellent problem-solving, attention to detail, and effective communication are valuable soft skills for this position. These abilities ensure secure, efficient, and accurate data sharing between organizations or systems, which is critical for business and operational success.

What is a Data Exchange job?

A Data Exchange job involves managing the transfer, integration, and security of data between systems, organizations, or platforms. Professionals in this role ensure data accuracy, compliance with regulations, and optimize data-sharing processes. They work with APIs, cloud services, and databases to facilitate seamless data flow. Strong technical skills in data management, security, and analytics are typically required.

What jobs make $1,000,000 a year?

In the field of data exchange, high-paying roles such as Chief Data Officer, Data Exchange Executive, or senior data platform architects can reach or exceed $1 million annually, especially in large corporations or tech firms. These positions typically require extensive experience, advanced skills in data management, and leadership responsibilities. Compensation at this level often includes base salary, bonuses, stock options, and other incentives.
What are popular job titles related to Data Exchange jobs in California? For Data Exchange jobs in California, the most frequently searched job titles are:
What job categories do people searching Data Exchange jobs in California look for? The top searched job categories for Data Exchange jobs in California are:
Data Exchange jobs near you
Infographic showing various Data Exchange job openings in California as of July 2026, with employment types broken down into 73% Full Time, and 27% Contract. Highlights an 61% In-person, 9% Hybrid, and 30% Remote job distribution.

AWS Data Architect

MSR Cosmos

Torrance, CA • On-site

$66.50 - $85.50/hr

Contractor

Re-posted 8 days ago

Job description

Role: AWS Data Architect

Location: Torrance CA Onsite-4 days a week

Duration: Long Term

Key Responsibilities

Data Architecture Design:

  • Architect and implement a scalable data hub solution on AWS using best practices for data ingestion, transformation, storage, and access control.
  • Define data models, data lineage, and data quality standards for the Datahub.
  • Select appropriate AWS services (S3, Glue, Redshift, Athena, Lambda) based on data volume, access patterns, and performance requirements.
  • Come up with a design that accommodates AI/ML applications in the next phase
  • Data Ingestion and Integration:
  • Design and build data pipelines to extract, transform, and load data from various sources (databases, APIs, flat files) into the Datahub using AWS Glue, AWS Batch, or custom ETL processes.
  • Implement data cleansing and normalization techniques to ensure data quality.
  • Manage data ingestion schedules and error handling mechanisms.
  • Data Governance and Access Control:
  • Establish data access controls and security policies to protect sensitive data within the Datahub using IAM roles and policies.
  • Develop data governance frameworks including data quality checks, data lineage tracking, and data retention policies.
  • Data Analytics Enablement:
  • Create data catalogs and metadata management systems to facilitate data discovery and understanding by business users and data analysts.
  • Design and implement data views and dashboards using Power BI to enable data exploration and visualization.
  • Create data warehouses and data marts to meet the needs of the business
  • Monitoring and Optimization:
  • Monitor data pipeline performance, data quality, and system health to identify and resolve issues proactively.
  • Optimize data storage and processing costs by leveraging AWS cost optimization features.
  • Data Exchange
  • Develop the required governance, security, monitoring and guard rails to enable efficient data exchange between internal application and their external vendors, partners, and SaaS providers
  • Develop intake process, SLAs, and usage rules for internal and external data set producers and consumers

Required Skills and Experience:

  • AWS Expertise: Deep understanding of AWS data services including S3, Glue, Redshift, Athena, Lake Formation, Sep Functions, CloudWatch and EventBridge.
  • Data Modeling: Proficiency in designing dimensional and snowflake data models for data warehousing and data lakes.
  • Data Engineering Skills: Experience with ETL/ELT processes, data cleansing, data transformation, and data quality checks. Experience with Informatica IICS and ICDQ is a plus.
  • Programming Languages: Proficiency in Python, SQL, and potentially Pyspark for data processing and manipulation.
  • Data Governance: Knowledge of data governance best practices including data classification, access control, and data lineage tracking.

Preferred Qualifications:

  • Experience with data lake house architectures and the ability to leverage both structured and unstructured data.
  • Familiarity with data visualization tools like Tableau or Power BI.
  • Strong communication and collaboration skills to work with stakeholders across business and technical teams.
  • AWS certifications related to data analytics and architecture.
Thanks
Ramesh