Staff Data Engineer, Data Platform

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Data Engineer, Data Platform in Spain. This role offers the opportunity to lead and shape the evolution of a modern data platform in a fast-growing SaaS environment. As a Staff Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and a data lakehouse that enables broad access for BI, machine learning, and engineering teams. You will collaborate across teams to support analytics use cases, migrate and modernize the data stack, and mentor other engineers to drive best practices. This position is ideal for an experienced engineer passionate about data architecture, distributed systems, and building production-grade solutions that empower decision-making and business growth. Your contributions will directly impact the company's ability to leverage data effectively at scale. Accountabilities: Own, design, and evolve the data platform, architecture, and tooling to meet analytics and product needs. Lead the delivery of a modern data lakehouse architecture, including prerequisite stream and batch data pipelines. Collaborate with Engineering, Product, and BI teams to enable new analytics use cases and migrations. Support and optimize existing data engineering systems for reliability and performance. Mentor and coach junior data engineers and backend engineers on best practices in data engineering. Ensure high-quality data availability and accessibility for BI, ML, and analytics teams. Establish standards for data modeling, ingestion, and processing across the organization. Requirements: 8+ years of professional experience in Data Engineering, including modern data stack expertise. 2+ years in a Staff or Lead engineering role with proven project leadership. 5+ years writing production-grade code, preferably in Go; familiarity with JVM languages (Java, Scala, Kotlin). Hands-on experience with modern data lakehouse technologies, including Iceberg, Hudi, or Delta Lake. Strong experience building and operating stream processing pipelines with Apache Spark and/or Flink. Expertise in AWS cloud architecture and a broad array of database technologies (Postgres, OLAP, NoSQL, etc.). Experience with event-driven distributed systems and remote startup environments. Excellent communication, project management, and cross-team collaboration skills. Proven track record of career growth, promotions, or leadership impact in prior roles. Experience in SaaS startups, ideally in growth-stage companies with 200+ employees and venture backing. Benefits: Competitive base salary ($200-235k) plus significant equity participation. Flexible work-from-home or remote arrangements. Opportunity to lead and shape a high-impact data platform in a fast-growing startup. Professional growth and mentorship opportunities within a collaborative team. Comprehensive healthcare coverage (health, dental, vision). Generous paid time off and flexible leave policies. Engaging and innovative company culture with strong focus on learning and impact. Why Apply Through Jobgether? We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best  Why Apply Through Jobgether?  Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.