Staff Data Engineer (Databricks specialist)

Jobgether; Spain; Remote; EUR 120,000 - 180,000; Full time

Benefits offered by this job

Fully remote work

Professional development

International collaboration

Career growth

Work-life balance

Job summary

Jobgether on behalf of a partner company seeks a Staff Data Engineer (Databricks Specialist) based in Spain. You will lead the design and development of scalable, enterprise-grade data platforms with a strong focus on Databricks and cloud-native technologies, guiding cross-functional data initiatives across ingestion, transformation, and delivery.

You will mentor engineers, shape enterprise data architecture, MDM, and AI-powered capabilities, while championing data governance, quality, and

Qualifications

• Bachelor's degree in computer science, engineering, or related field.
• 12+ years in data or software engineering with enterprise-scale platforms.
• Expert SQL and Python; Scala/Java a plus.
• Extensive Databricks and cloud data platform experience.
• MDM design, entity resolution, reference data, hierarchies.
• Mentoring and leading large technical initiatives.
• Strong communication and cross-team collaboration.

Responsibilities

• Own architecture of cross-functional data initiatives across ingestion, transformation, storage, and serving layers.
• Design and maintain scalable data pipelines with Databricks on cloud platforms.
• Lead MDM initiatives including golden records and entity resolution.
• Architect AI and LLM-powered solutions; integrate RAG pipelines and copilots.
• Build data foundations for ML/AI; manage feature stores and embeddings.
• Deliver backend data services and APIs (REST/GraphQL); ensure data accessibility.
• Promote data governance, quality, testing, observability, and CI/CD.
• Mentor senior engineers and drive technical direction across teams.
• Define scalable data roadmaps with product/analytics leadership.

Skills

SQL

Python

Databricks

Cloud data platforms

MDM

AI/LLM

Leadership/mentoring

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Snowflake

Azure/AWS/GCP

REST/GraphQL APIs

LangChain/AI tooling

dbt

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Engineer (Databricks Specialist) based in Spain.

We are seeking an experienced Staff Data Engineer to lead the design and development of scalable, enterprise-grade data platforms, with a strong specialization in Databricks and modern cloud technologies. In this strategic role, you will drive complex, cross-functional data initiatives, ensuring reliable data ingestion, transformation, storage, and delivery. You will play a key role in shaping enterprise data architecture, Master Data Management (MDM), and AI-powered data capabilities. Working closely with engineering, product, and analytics leaders, you will translate business needs into innovative and scalable technical solutions. You will also champion engineering excellence, data governance, and platform performance while mentoring experienced engineers. This is an opportunity to influence technical direction, accelerate AI adoption, and build the foundations for next-generation data-driven solutions.

Accountabilities:

• Own and drive the technical architecture of complex, cross-functional data initiatives, covering ingestion, transformation, storage, and serving layers.
• Design, develop, and maintain scalable, high-performance data pipelines and distributed data platforms using Databricks and cloud-native technologies across Azure, AWS, or GCP.
• Lead enterprise Master Data Management (MDM) initiatives, including golden records, entity resolution, match-and-merge processes, data domains, reference data, hierarchies, and data stewardship.
• Architect and integrate agentic AI and LLM-powered solutions, including autonomous agents, RAG pipelines, AI copilots, and orchestration frameworks, into enterprise data platforms.
• Build and maintain data foundations for machine learning and AI applications, including feature stores, vector databases, embeddings, and ML/LLMOps pipelines.
• Design and deliver backend data services and APIs using REST or GraphQL, ensuring curated datasets are accessible to applications, analytics, and business intelligence platforms.
• Establish and promote engineering standards covering data modeling, quality, testing, observability, CI/CD, deployment, and responsible AI-assisted development.
• Implement enterprise-wide data governance, lineage, cataloging, and quality frameworks to ensure data consistency, reliability, and transparency.
• Lead technical design reviews, provide architectural guidance, and influence engineering decisions across multiple teams.
• Collaborate with product, analytics, and engineering leadership to define scalable data roadmaps aligned with business objectives and AI-driven opportunities.
• Identify and resolve systemic performance, reliability, and scalability challenges across the data ecosystem.
• Mentor and coach senior and mid-level engineers, promoting technical excellence and best practices in data engineering, MDM, and AI.
• Evaluate emerging technologies, frameworks, and industry trends to continuously improve platform capabilities, engineering efficiency, and resilience.

Requirements:

• Bachelor's degree in Computer Science, Engineering, Management Information Systems, or a related discipline is preferred.
• 12+ years of professional experience in data engineering or software engineering, with a proven track record of architecting enterprise-scale data platforms and pipelines.
• Expert-level SQL skills and strong proficiency in Python. Experience with Scala or Java is an advantage.
• Extensive hands-on experience with Databricks and modern cloud data platforms such as Snowflake, Azure Synapse, BigQuery, or Amazon Redshift.
• Strong understanding of cloud-native architecture, distributed systems, data modeling methodologies (dimensional modeling, Data Vault, Lakehouse), and ETL/ELT architectures.
• Proven experience designing and implementing enterprise MDM solutions, including entity resolution, match-and-merge, golden records, reference data, and hierarchy management. Familiarity with Informatica, Reltio, Profisee, or similar platforms is highly valued.
• Practical experience building or integrating agentic AI systems, LLM-powered applications, RAG pipelines, and AI agent orchestration frameworks such as LangChain, AutoGen, Semantic Kernel, or MCP.
• Experience developing backend data services and REST/GraphQL APIs, with the ability to contribute across the technology stack.
• Strong knowledge of relational and NoSQL databases, as well as modern data lake and lakehouse formats such as Delta Lake, Apache Iceberg, and Parquet.
• Deep understanding of CI/CD pipelines, Infrastructure as Code (IaC), DevOps, and DataOps practices.
• Demonstrated ability to lead large-scale technical initiatives involving multiple teams and stakeholders.
• Excellent communication, collaboration, and problem-solving skills, with the ability to influence technical decisions without direct managerial authority.
• Proven mentoring and coaching capabilities, with a passion for developing engineering talent and promoting knowledge sharing.

Nice to have:

• Experience with data governance, lineage, and cataloging solutions such as Unity Catalog, Microsoft Purview, Collibra, or Alation.
• Knowledge of multi-agent architectures, tool-calling systems, and advanced RAG implementations.
• Experience with event-driven architectures and real-time data processing technologies such as Kafka, Azure Event Hubs, Amazon Kinesis, Flink, or Spark Structured Streaming.
• Experience building data layers for AI and machine learning, including feature stores, vector databases, embeddings, and ML/LLMOps solutions.
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes, as well as workflow orchestration tools like Airflow, Dagster, and dbt.
• Previous experience in commercial real estate, fintech, or complex operational and transaction-based environments.
• Technical thought leadership demonstrated through conference speaking, technical publications, or open-source contributions, particularly in applied AI and modern data engineering.

Benefits:

• Fully remote work: Enjoy the flexibility to work from anywhere, with a digital-first approach and opportunities to collaborate with international teams.
• Work-life balance: Benefit from flexible working arrangements that support your personal and professional commitments.
• Meaningful projects: Contribute to challenging, high-impact projects across different industries and work with modern technologies.
• Continuous learning: Access ongoing professional development opportunities, hands‑on technical challenges, and opportunities to expand your expertise.
• International collaboration: Join a diverse, multicultural team of talented professionals who value creativity, innovation, and knowledge sharing.
• Career growth: Develop your technical leadership capabilities and help shape the future of enterprise data engineering and AI‑driven solutions.
• Full‑time opportunity: Join a team working on long‑term, impactful data engineering initiatives.

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.

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