Top Remote Data Engineer Jobs in San Antonio, TX

Design and manage financial systems for accurate cashback calculations, build and maintain reconciliation processes, ensure data integrity for yield-bearing instruments, collaborate with compliance, and partner with cross-functional teams to improve financial system efficiency.

Manage, design, and optimize data activities for federal IAM systems. Develop data models, file layouts, source-to-target mappings, data dictionaries, integrations, ETL processes, and analytics support for identity analysis and fraud detection. Administer and tune databases, including configuration, backups, monitoring, capacity planning, and performance optimization. Support secure handling of identity and PII data, network-related data flows, documentation, token management processes, and collaboration across development, security, and operations teams.

Design, build, and maintain data warehouse infrastructure, semantic/dimensional models, metrics layer, and BI dashboards (Sigma, Power BI, Databricks). Build secure ELT pipelines, enforce governance and row-level security (Entra ID), enable self-service analytics and AI/ML integrations, triage BI issues, train stakeholders, and collaborate in Agile to deliver reliable, performant reporting and curated data products.

Build and maintain scalable data platforms, pipelines, observability metrics, metadata-driven solutions, data transformations, and third-party integrations. Collaborate with data scientists, analysts, DevOps, and business stakeholders to deliver accurate, timely data and meaningful insights. Responsibilities include optimizing workflows, implementing infrastructure as code, and supporting cloud-based data systems.

Build and maintain scalable data platforms, pipelines, observability metrics, metadata-driven solutions, data transformations, and third-party integrations. Collaborate with data scientists, analysts, DevOps teams, and business stakeholders to deliver timely, accurate data and meaningful insights. Responsibilities include optimizing transformations, implementing infrastructure as code, and administering or tuning Snowflake environments.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Design, build, and maintain Keboola-based data pipelines integrating multiple business systems to deliver accurate, scalable data for supply chain, logistics, and transportation analytics; collaborate with analysts and engineers; support documentation, governance, and pipeline automation.

Support design, development, and maintenance of data pipelines and infrastructure. Assist with ETL/ELT workflows, data ingestion, cleaning, validation, modeling, and warehousing. Document processes and collaborate with data teams to support analytics use cases.

Designs, deploys, and supports healthcare data acquisition, integration, transformation, and data quality solutions using enterprise and cloud technologies. Develops SQL assets, OMOP Common Data Model transformations, testing processes, documentation, and AI data pipelines. Manages projects, resolves escalated incidents, mentors data engineers, supports training, and collaborates with analysts, vendors, clients, and technology teams.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Designs, develops, and maintains scalable data pipelines and workflows using Matillion, HVR, and Databricks. Performs data modeling, SQL-based transformation, ETL/ELT optimization, and data quality management. Collaborates with data scientists, analysts, architects, and business data owners to translate requirements into secure, governed data solutions. Documents processes and ensures compliance with security and regulatory standards, including U.S. government cloud requirements.

The Snowflake Data Engineer will work on data cleansing and harmonization, moving from legacy systems to SAP S4, focusing on ETL/ELT development and view creation.

This role involves designing, building, and maintaining data pipelines on Snowflake. Responsibilities include ensuring data quality and collaborating with stakeholders to deliver solutions.

The AWS Data Engineer will work on a data cleansing and harmonization project, focusing on AWS ETL design and development using various AWS services.

The Snowflake Data Engineer will design, build, and maintain data pipelines on Snowflake, optimizing performance and ensuring data quality while collaborating with stakeholders.

The Snowflake Data Engineer and Product Owner will manage the Snowflake data analytics project, collaborating with stakeholders, leading Agile practices, and ensuring quality deliverables through effective team coordination and backlog management.

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

Build and maintain ETL/ELT data pipelines and storage for batch and real-time use. Partner with product and engineering to define requirements, ensure data quality, monitor pipeline health, integrate cloud data warehouses/lakes, optimize SQL/Python transformations, and document data flows and architecture.

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

Design, build, and maintain scalable batch and streaming data pipelines, cloud infrastructure, and the Enterprise Data Hub. Partner with stakeholders to productionize ingestions, ensure data quality, implement metadata/catalog solutions, mentor junior engineers, and support analytics and ML workloads using cloud and big-data tooling.

Maintain and monitor Snowflake data warehouse and ingestion pipelines. Troubleshoot file/load/data quality issues, operate SFTP/drop-zone/file automation, support scheduled loads, build dbt models and tables, document runbooks, and serve as backup for core warehouse operations while collaborating with engineering and IT.

The role involves architecting and improving data systems, defining governance standards, optimizing performance, and mentoring engineers in data engineering.

The Data Engineer designs, builds, and optimizes enterprise data pipelines, lakes, warehouses, integrations, and analytics infrastructure. Responsibilities include ELT development using Snowflake and Informatica, data governance, quality, security, performance monitoring, PII protection, cost optimization, and support for analysts and data scientists. The role also delivers process improvements, analytics tools, stakeholder collaboration, technical mentoring, and scalable data architecture across cross-functional teams.

The ClaimsXM Data Engineer III role has limited responsibilities listed. The position requires U.S. citizenship or naturalized citizenship and requires all work to be completed within the continental United States, Alaska, or Hawaii.