elt jobs in San Diego

Senior software engineer responsible for designing, developing, and maintaining cloud-based backend systems and data pipelines for medical device software at Dexcom. You'll build distributed systems, APIs, and ETL/ELT pipelines that ingest and transform large-scale data, integrate AI insights, and serve internal systems and external partners.…See more The role requires 5–8 years of experience with general-purpose programming (Java/Kotlin/Scala preferred), cloud platforms (AWS/Azure/GCP), CI/CD, and data platform architecture, with mentorship of junior engineers expected.

This is an onsite production support role for enterprise analytics platforms, requiring 5+ years of experience supporting Matillion, Cognos, Power BI, Tableau, and MDM environments. The specialist will act as the primary point of contact for analytics, BI, ETL, and MDM issues, coordinating between end users, business stakeholders, and offshore teams while managing daily operational health, incident response, and SLA performance.…See more The role demands expertise in cloud analytics platforms (AWS, Azure, Snowflake), ITIL-based service management, and ticketing systems like ServiceNow or Jira, with strong skills in incident/problem/change management and translating technical issues for business audiences.

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.

Staff Engineer who will design, build, and operate the Forge Platform—a distributed-systems foundation serving autonomy, ML Ops, simulation, and application teams. You will own architecture and technical standards for workflow orchestration, asynchronous processing, event-driven systems, and long-running service workflows while remaining hands-on in implementation, production troubleshooting, and reliability improvement.…See more Required: strong production experience with distributed systems, cloud-native platforms, or backend infrastructure; fluency in Go and Python; deep understanding of failure handling, consistency, fault tolerance, and state management; and ability to turn recurring infrastructure needs into reusable platform capabilities. You will work across Kubernetes, service networking, observability, and data pipelines to enable downstream teams to move faster on mission-critical systems.

Staff Engineer responsible for designing, building, and operating the Forge Platform—a distributed-systems foundation serving autonomy, ML, simulation, and test teams. You will architect cloud-native backend infrastructure, establish reusable platform capabilities, define technical standards, and remain hands-on in production troubleshooting, performance analysis, and reliability improvement.…See more Required: deep expertise in production distributed systems, Go and Python, workflow orchestration, and the ability to translate complex architecture into usable interfaces across multiple downstream teams.

Sr. Manager overseeing a data engineering team with responsibility for hiring, coaching, and performance management while remaining hands-on with architecture, design reviews, and technical decisions.…See more The role requires designing and operating production data pipelines and lakehouse platforms using AWS (S3, Glue, Athena, Lambda) and Snowflake, with hands-on proficiency in SQL and Python. Responsibilities include establishing data governance, compliance, security controls, CI/CD practices, and collaborating across engineering, analytics, product, and clinical teams to translate requirements into platform capabilities. The manager must balance delivery priorities, technical debt reduction, operational excellence, and emerging-technology evaluation while driving outcomes that affect broader business objectives.

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

Senior architect responsible for designing and leading enterprise-scale data platforms on Databricks and AWS, including cloud modernization, data migration, and lakehouse architecture. Requires deep expertise in PySpark, advanced SQL, Delta Lake, and data warehousing patterns, with accountability for technical strategy, solution design, and mentoring engineering teams.…See more Will drive CI/CD practices, data governance frameworks, data quality standards, and technical decision-making across complex data infrastructure initiatives. Expected to engage senior stakeholders, manage client relationships, and champion AI-powered engineering tools for productivity and automation.

Design, build, and maintain secure enterprise data platforms supporting AI/ML workloads, with responsibility for database optimization, CI/CD automation, and DoD compliance. Mentor junior engineers and provide technical leadership on architecture decisions.…See more Implement security controls aligned with NIST 800-53, RMF, and DISA STIG standards throughout the platform lifecycle. Develop ETL/ELT pipelines, support data lakes and lakehouses, and evaluate emerging data technologies for mission fit.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and customer experiences. Responsibilities include implementing end-to-end AI/ML pipelines using AWS services (SageMaker, Lambda, ECS/EKS), feature engineering with Snowflake, model fine-tuning and testing, and monitoring production performance.…See more The role requires 3+ years of AI/ML experience with 1–2 years in generative AI or LLMs, hands-on cloud deployment experience, and proficiency in Python, PyTorch, TensorFlow, or Hugging Face Transformers.

RIVO is seeking a Senior Data Platform Engineer to architect and build a modern enterprise data platform supporting analytics, machine learning, and near real-time processing. You will design the foundational data warehouse or lakehouse architecture, modernize legacy ETL processes, implement CDC-based ingestion and low-latency pipelines, and establish data quality and governance frameworks.…See more This role requires 8+ years of data warehousing or platform engineering experience, expertise in cloud platforms (Snowflake, Databricks, Azure), SQL and Python proficiency, and the ability to support both analytics and data science workloads at enterprise scale.

Design and build production ETL/ELT pipelines ingesting data from databases, APIs, applications, and Microsoft 365 sources into Azure Databricks and Power BI. Own code quality, CI/CD automation, testing strategies, monitoring, and data validation across development, test, and production environments in Azure DevOps.…See more Develop transformations and curated data products for analytics and AI applications, including secure document ingestion, metadata indexing, and telemetry. Collaborate with business and technical stakeholders to communicate progress, data limitations, and risks while maintaining runbooks and technical documentation.

Senior software engineer focused on building cloud-based backend services and data platforms for medical device systems at Dexcom. Design and develop end-to-end data pipelines supporting large-scale ingestion, transformation, and storage, while building and maintaining APIs that expose data to internal systems, partners, and mobile apps.…See more Collaborate with Data Engineers, AI/ML Engineers, and Platform teams to integrate AI insights into production systems, ensuring high standards for reliability, performance, scalability, and data quality. Lead through code reviews, design mentorship, and technical guidance while contributing to architecture decisions and long-term platform roadmap.

This role designs and governs enterprise data architectures across SQL, NoSQL, and cloud platforms for a financial institution. The Data Architect will establish data standards, lead golden-record and SSOT initiatives, architect ETL/ELT pipelines, manage data quality and governance frameworks, and oversee database platform strategy (SQL Server, Azure SQL, Snowflake, MongoDB Atlas, Cosmos DB).…See more The position requires 12+ years of progressive experience, deep cloud data platform expertise, SQL and Python proficiency, and demonstrated leadership guiding engineering teams through enterprise modernization and compliance-driven initiatives.

Senior Enterprise Data Engineer role requiring 5+ years designing and developing OLTP/OLAP databases, ETL/ELT pipelines using SSIS, Azure Data Factory, or Python, and enterprise reporting solutions with Power BI and SSRS. Must have advanced SQL Server expertise, strong data warehousing and dimensional modeling knowledge, and experience in Agile environments.…See more Preferred qualifications include Azure data platforms (Synapse, Data Lake, Fabric), Databricks, Apache Spark, Azure DevOps, and CI/CD practices.

Senior Enterprise Applications Developer responsible for designing, delivering, and supporting complex enterprise software, integrations, data solutions, and automation across cloud and on-premises environments. Requires 7+ years of progressive experience with advanced Python proficiency, hands-on expertise in REST APIs, ETL/data pipelines, CI/CD practices, and AWS or Azure cloud-native development.…See more Must demonstrate ability to lead solution design from requirements through production support, with experience in workflow automation, AI/LLM integrations, and compliance frameworks (HIPAA, SOC 2, SOX). Strong emphasis on security, governance, architecture, and cross-functional collaboration with technical teams and business leaders.

Design, build, and maintain scalable data pipelines and platforms that power high-volume, data-driven applications. Develop and optimize ETL/ELT processes for large, complex datasets using Databricks and Spark, and build backend data services in C# / .NET.…See more Lead technical design decisions, mentor engineers, and leverage AI-assisted coding tools to improve engineering efficiency. Requires 5+ years of data engineering experience, strong expertise with data pipelines and ETL frameworks, and hands-on experience with AWS-based data platforms.

Staff Data Engineer at Illumina seeking a senior individual contributor with 10+ years building and scaling data products on Databricks and Snowflake. The role spans end-to-end ownership of data pipelines across Supply Chain, Manufacturing, and Quality domains, requiring advanced Python, SQL, and data modeling skills with hands-on expertise in Spark, Delta Lake, dbt, and distributed systems design.…See more Responsibilities include designing medallion-architecture data products, embedding governance and data quality, adopting AI in analytics workflows, and mentoring a global engineering team. The candidate will set technical standards, lead architecture decisions, and communicate trade-offs across business, AI, and platform stakeholders.

This Data Engineer II role focuses on data operations and infrastructure, supporting the transition of data systems from development to production. The engineer will administer data lakehouse/warehouse platforms (Snowflake, Databricks, Redshift, BigQuery, Azure Synapse), manage RBAC and user governance, monitor and troubleshoot data pipelines, and contribute to data governance and quality best practices.…See more Key responsibilities include orchestration tool administration (Apache Airflow, dbt), observability framework development, incident management, and hands-on SQL and Python work to maintain and optimize production data systems.

Principal Engineer leading the design, build, and operation of an enterprise data platform serving 50+ source systems across R&D, Commercial, Manufacturing, and other business functions. The role combines hands-on data engineering (PySpark, T-SQL, Python, Data Factory, medallion architecture) with technical leadership of data engineers, vendor management, platform standards enforcement, and cross-functional stakeholder partnership.…See more Responsibilities span CI/CD pipeline design, data quality and reliability instrumentation, semantic layer development, data governance implementation, and delivery of new source-system integrations at scale.

Clinical Data Engineer II/III will develop and maintain data transformation models across clinical schemas, ensuring data quality, reliability, and regulatory compliance in a healthcare environment. The role requires designing data contracts, building reconciliation logic to unify multi-source data, and owning clinical result data end-to-end from ingestion through monitoring.…See more You will partner with clinical operations, regulatory, and research teams to resolve data issues, maintain dashboards subject to formal validation, and serve as a subject-matter expert on the warehouse clinical data. This position demands 5+ years of hands-on data engineering with production transformation frameworks (dbt preferred), deep SQL expertise, and demonstrated experience in regulated environments.

As a Sr. Technical Product Manager for Data at Petco, you will own the vision, roadmap, and delivery of enterprise data products that power analytics, personalization, and AI-driven decision-making across the organization.…See more You'll translate business needs into technical requirements, define data-quality standards and governance practices, and partner with data engineers, architects, analysts, and business stakeholders to build trusted, reusable data products. The role requires 5+ years of product management experience with strong technical depth in data warehousing, ETL/ELT, SQL, and data modeling, plus expertise managing Agile backlogs and cross-functional delivery on modern cloud platforms like Google Cloud and BigQuery.

Sr. Technical Product Manager who will own the vision, roadmap, and delivery of enterprise data products across Petco's business domains (customer, loyalty, sales, inventory, marketing, finance).…See more The role bridges business stakeholders with data engineering, analytics, architecture, and governance teams—translating requirements into data models, defining quality standards, data contracts, and metric definitions. You'll drive adoption of governed data products built on Google Cloud and BigQuery, manage cross-functional delivery, and champion data governance practices. Required: 5+ years of product management with technical product ownership or data product management experience, strong SQL and data warehousing expertise, and proficiency with ETL/ELT, APIs, data quality, and BI tools.

Own and administer a Microsoft Fabric environment including lakehouses, OneLake storage, workspaces, and SQL Analytics endpoints. Design and maintain scalable semantic models, Power BI reports, and dashboards across finance, investor relations, and operations.…See more Lead migration of Yardi-native Power BI reporting to Fabric and replace manual Excel-driven reporting with governed solutions. Build AI-enabled analytics, natural-language querying capabilities, and establish governance standards for data access, row-level security, and workspace administration.

Design, build, and maintain data pipelines that ingest, transform, and load data from SQL Server, PostgreSQL, SaaS platforms like HubSpot, and internal applications into Snowflake. Develop and optimize data models, manage data quality and governance, and create dashboards and reports to support reporting and analytics use cases.…See more Collaborate with business stakeholders to gather requirements and translate them into scalable data solutions. Optimize query performance and storage efficiency within Snowflake while implementing best practices in documentation and pipeline monitoring.