data-architecture jobs in San Diego

Designs enterprise data fabric solutions that provide unified, intelligent access to distributed data across on-premises and multi-cloud environments, integrating data virtualization, active metadata, knowledge graphs, cataloging, and automated integration. Establishes reference architectures, integration patterns, and governance that scale across enterprises, enabling self-service data consumption and real-time delivery.…See more Applies modern data paradigms including data mesh, data products, and cloud platforms to advise clients on major data modernization initiatives. Requires minimum 10 years in data architecture, 6 years architecting data fabric solutions, 5 years with cloud data platforms, and 4 years with data integration/ETL tooling.

Principal Engineer Data will develop and execute a data architecture strategy aligned with business goals, building and maintaining data models, metadata standards, and integration frameworks. The role requires leading technical assessments for digitizing core business functions, working with stakeholders to translate requirements into architectural solutions, and ensuring data storage, retrieval, and governance meet enterprise standards.…See more The candidate must have a STEM degree with at least 5 years of experience (or Master's with 3 years), strong expertise in SQL Server, data visualization tools (Tableau, Power BI), and data architecture principles including data integration, governance, and security protocols.

Principal-level Business Intelligence Architect responsible for designing and leading enterprise data architecture, ETL pipelines, and reporting infrastructure for a healthcare organization. The role requires 8+ years of BI/data management experience with at least 4 years leading individual contributors and managers, deep expertise in SQL, relational and NoSQL databases, and cloud/streaming data architectures.…See more You will mentor technical teams, communicate complex data solutions to executive stakeholders, ensure HIPAA compliance, and drive innovation in data strategy across a matrix organization.

Senior Data Architect with 15+ years of experience designing and implementing enterprise data platforms that support modern AI/ML and Generative AI applications. Must have strong hands-on expertise in ETL/ELT, Python, SQL, and enterprise data warehousing, with production experience in Treasure Data, real-time analytics, streaming pipelines (Apache Kafka), and AI-ready data architectures including RAG, vector databases, and LLM integrations (LangChain, LangGraph, Azure OpenAI, AWS Bedrock).…See more Will design batch and real-time enterprise data architectures on cloud platforms (AWS, Azure, GCP, Snowflake, Databricks) with CDC/Debezium incremental processing capabilities.

Design and review data engineering solution architectures on Databricks and AWS, aligning technical decisions with business goals. Lead enterprise-scale data migration and modernization programs, providing architectural guidance and technical leadership across client and internal teams.…See more Demonstrate hands-on expertise in PySpark, SQL, data warehousing, CI/CD pipelines, and data governance frameworks. Mentor team members and foster a knowledge-sharing culture while driving smooth project execution and transition.

The role seeks a Databricks & AWS Data Engineering Architect to lead enterprise-scale data migration and modernization programs for a banking client. The architect will design and implement data solutions using Databricks, PySpark, SQL, and AWS, with responsibility for CI/CD pipelines, data governance frameworks, and data quality monitoring.…See more Required skills include hands-on expertise in data engineering, data warehousing, and data architecture, along with leadership capabilities to manage stakeholders and drive engineering best practices across the organization.

Lead a Data Engineering team to establish modern DataOps and CI/CD practices, mentor engineers in PySpark, SQL, dbt, Fivetran, and cloud-native development, and design scalable data infrastructure across GCP, Azure, and AWS cloud data warehouses (BigQuery, Snowflake, Databricks). Manage technical delivery, collaborate across enterprise teams to develop end-to-end data solutions, and align data initiatives with business goals while remaining current on industry trends.See more

Design and review data engineering solution architectures on AWS and Databricks, aligning technical decisions with business goals and market trends. Lead enterprise-scale data migration and modernization programs, mentoring teams and driving initiatives from proposal through delivery.…See more Provide hands-on expertise in Databricks, PySpark, SQL, and AWS, with strong proficiency in CI/CD pipelines, data governance, and engineering best practices. Engage with clients and internal stakeholders to build productive relationships and ensure successful project execution.

This role is a Data Engineering Architect responsible for designing and reviewing enterprise-scale data architectures on Databricks and AWS, leading migration and modernization programs, and resolving complex technical challenges during build and deployment phases. The architect will provide strategic insights to development teams and clients, establish data governance frameworks, monitor system performance, and contribute to proposals and RFPs.…See more Required expertise includes hands-on proficiency in Databricks, PySpark, SQL, AWS, CI/CD pipelines, and data architecture best practices, with proven experience in enterprise-scale programs and strong technical leadership and stakeholder management skills.

Lead a Data Engineering team to establish modern DataOps and CI/CD practices while providing technical mentorship in PySpark, SQL, dbt, and Fivetran. Design and optimize scalable, reliable data infrastructure across cloud and on-premise ecosystems (AWS, GCP, Azure) using Databricks, BigQuery, and Snowflake.…See more Manage end-to-end data sourcing, processing, integration, and delivery projects to meet business objectives and predetermined success criteria. Require 10+ years managing Data Engineering teams and 7+ years working with cloud-native data platforms and advanced SQL/Python/PySpark expertise.

Lead a data engineering team responsible for building scalable data pipelines, trusted datasets, and reusable data products powering analytics, experimentation, and AI across Scribd. This role blends technical leadership with hands-on architecture guidance; you'll establish engineering standards, drive design reviews, mentor engineers, and partner cross-functionally to translate business needs into production-grade data solutions.…See more Requires 10+ years in data engineering or data platforms, 3+ years leading engineering teams, deep expertise in dimensional modeling and scalable data architectures, and strong SQL plus Python/Scala skills. You'll work with modern cloud data platforms like Databricks, Snowflake, and BigQuery, and distributed processing frameworks like Spark.

Own the product direction, roadmap, and prioritization for a ground-up AI-accelerated migration platform that helps law firms move onto the CARET Legal practice management system. You will translate complex migration and onboarding challenges into well-scoped product opportunities, work closely with an Engineering Tech Lead on technical architecture, and partner with migration/operations teams to deliver measurable customer and business outcomes.…See more The role requires deep technical fluency with data flows and system behavior, strong judgment about scope and tradeoffs, and the ability to engage directly with engineers and cross-functional stakeholders. You'll define success metrics around time-to-value, cutover experience, delivery predictability, and quality while balancing platform investment with customer commitments.

Design and implement enterprise data architecture solutions across on-premises and cloud environments, including data models, pipelines, governance frameworks, and integration patterns. Develop data pipeline blueprints, entity relationship diagrams, and manage data warehousing, cataloging, and quality standards.…See more Serve as a subject-matter expert for data architecture across DoD analytics platforms, Microsoft 365, and hybrid cloud environments. Coordinate with government technical leads, platform teams, and data stakeholders while managing data governance, security accreditations, and administrative requirements.