Top Data Engineer Jobs in Valencia

Design and scale mission-critical market data services for stocks, options, crypto, and foreign exchange. Responsibilities include architecting backend systems and APIs, maintaining software quality and test coverage, participating in code reviews, and troubleshooting incidents and bugs. The role uses Go and Python with REST, gRPC, WebSockets, SSE, Docker, Kubernetes, Google Cloud, BigTable, Prometheus, Grafana, and ELK.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Own, run and evolve the Data Privacy Orchestrator that manages data retention, deletion, anonymization and pseudonymization. Build safe-by-default platform abstractions, self-serve tooling, docs and observability; operate production (deploys, alerting, on-call), align legal/security/product, and extend platform coverage across data stores and third parties as the company expands.

Build and maintain Snowflake-based data assets and metrics layers using dbt, SQL, and Python. Design reliable data models and pipelines, enable self-service analytics, collaborate with stakeholders, document definitions and best practices, and deliver scalable analytics solutions.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Lead design and implementation of scalable, real-time data infrastructure. Build and optimize production-grade streaming pipelines, employ spec-driven development and agentic AI workflows, implement testing/monitoring, take ownership of systems, and mentor junior engineers.

Design, build, and operate high-frequency, event-driven data pipelines into Snowflake; implement reverse ETL; model data with dbt; deploy cloud infra as code; monitor and improve production reliability, latency, quality, and cost; mentor teammates and establish data engineering standards.

Design, build, and maintain streaming ingestion pipelines and migrate SaaS pipelines to in-house infrastructure. Deliver resilient, idempotent data into Snowflake, improve AWS streaming stack, manage IaC with Terraform, monitor and troubleshoot production pipelines, and collaborate on safe data access for AI tooling.

Design and build a scalable cloud data platform on Google Cloud, create reliable batch and streaming ETL/ELT pipelines, enforce data quality and observability, automate IaC/CI-CD, and support analytics, ML, and product teams with high-quality data.

Design, build, and scale high-performance data pipelines and infrastructure (ingestion, transformation, storage, modeling, serving) using ClickHouse, Postgres, Python and dbt. Manage data quality, reliability, and observability at terabyte and 500M+ address scale, collaborate with researchers and product, mentor engineers, and leverage AI tools to accelerate work.

Own and evolve the enterprise LookML semantic layer, build scalable Looker data products, optimize performance and governance across Looker instances, translate stakeholder needs into reusable models, mentor junior developers, and support conversational analytics and AI-driven queries.

Own and evolve the core data platform: warehouse design, dbt transformations, and production AWS pipelines. Refactor and harden API-driven data flows, ensure observability and testing, partner with backend and product teams, and contribute to data-aware backend features to deliver reliable, product-focused data.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

The Senior Data Engineer will lead the design and evolution of scalable data architectures, mentor team members, build data pipelines, and integrate Generative AI into workflows.

Seeking a Senior Data Support Engineer with 5-6 years of experience in Data Engineering, specifically utilizing Snowflake, Python, SQL, and AWS for data manipulation, warehousing, and testing processes.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.

Lead design and implementation of a cloud data platform on Azure. Build ingestion and transformation pipelines (Data Factory, Databricks), enable downstream reporting/APIs (SQL, Cosmos, Synapse), automate deployments (ARM templates, DevOps), advise on data models, integration, security, and BI, and collaborate with architects and engineers to deliver short- and long-term enterprise data solutions.

Lead design and implementation of a cloud data platform: plan milestones, build Azure Data Factory pipelines and Databricks transformations, integrate diverse data stores (SQL, Cosmos DB, Synapse), automate deployments (ARM templates, DevOps), advise on data models, APIs, security, and BI, and provide short-term solutions and best practices for enterprise data needs.

The Tableau Developer will design, build, and maintain Tableau dashboards, optimizing performance and ensuring data accuracy while collaborating with stakeholders.

Build end-to-end features for a data orchestration platform across Java/Micronaut backend and Vue 3/TypeScript frontend. Implement data-aware orchestration (assets, lineage, freshness, quality), create integrations/plugins (dbt, Fivetran, Airbyte, warehouses), improve UI (flow editor, topology, dashboards), collaborate on 8-week releases, review PRs, and engage with the open-source community.

As a Senior Data Engineer, you will deliver complex projects, manage customer relationships, and mentor junior engineers while using Databricks and various cloud platforms.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Build and own end-to-end features for Fever's native Android app: shape product with PM/Design, implement Kotlin/Compose solutions in a multi-module Gradle codebase, integrate APIs and payment SDKs, instrument experimentation/analytics, iterate from data, and bridge AI/data capabilities into the user experience.

Own and operate Databricks-based data platform production support, build and migrate ETL/ELT pipelines to Databricks across Azure/AWS, optimize compute and performance, enforce Delta Lake architecture and data security, implement observability and CI/CD, support multi-tenant onboarding and on-call incident response, and maintain runbooks and SLA metrics.