Senior Specialist - Data Engineering

Location: Madrid, Spain; London, United Kingdom; Berlin, Germany; Brussels, Belgium; Paris, France; Rome, Italy; Munich, Germany; Frankfurt, Germany; Lisbon, Portugal; Düsseldorf, Germany; Stuttgart, Germany; Cluj-Napoca, Romania. Hybrid work is required, with at least three days per week in the local office or onsite with clients.

Company

hirify.global provides risk, reinsurance, capital, people, investments, and management consulting services to clients in 130 countries.

What you will do

• Provide hands-on technical leadership for the Vulcan Platform Team, including mentoring engineers, setting engineering standards, and supporting architecture decisions.
• Design, build, and maintain scalable, resilient, secure, and cost-efficient platform capabilities using AWS and Databricks.
• Develop reusable platform services, lakehouse and event-driven architectures, data pipelines, ingestion frameworks, and transformation workflows.
• Improve automation, infrastructure as code, CI/CD, observability, monitoring, alerting, logging, incident response, and operational maturity.
• Collaborate with product, architecture, security, business, data consumer, and domain teams to deliver governed and reusable data products.
• Embed security, compliance, governance, data quality, lineage, and access-control requirements into engineering solutions.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related discipline, or equivalent practical experience.
• Significant experience in software engineering, platform engineering, or data engineering, including demonstrable senior or lead-level experience.
• Strong hands-on experience designing and delivering AWS solutions and working with Databricks or similar data lakehouse technologies in enterprise data or platform environments.
• Proven experience building and supporting scalable data pipelines, distributed processing workloads, and cloud-native platforms.
• Experience leading engineers and driving technical delivery across cross-functional teams.
• Experience with platform automation, CI/CD pipelines, infrastructure as code, DevOps tooling, containerisation, and workflow orchestration.
• Strong knowledge of AWS storage, compute, orchestration, monitoring, and security services, including S3, Lambda, Glue, Step Functions, RDS, IAM, and CloudWatch.
• Strong experience with Databricks notebooks, workflows, cluster management, and data processing patterns; good understanding of Spark and distributed data processing.
• Strong programming capability in Python and SQL, plus experience with data architecture, data modelling, modern lakehouse principles, Git, logging, metrics, monitoring, and alerting.
• Strong leadership, stakeholder management, communication, problem-solving, analytical, and influencing skills, with the ability to work across multiple priorities.
• Experience operating in governed enterprise environments with an understanding of security, risk, and compliance requirements.

Nice to have

• Experience in financial services, insurance, pensions, or other regulated environments.
• Experience supporting shared platforms used by multiple product or domain teams.
• Exposure to data governance, metadata, lineage, and access-control frameworks.
• AWS certifications such as AWS Certified Solutions Architect or AWS Certified Data Engineer.
• Databricks certification.

Culture & Benefits

• Hybrid work combining remote flexibility with office collaboration and professional development.
• At least three days per week in the local office or onsite with clients; office-based teams have at least one weekly anchor day.
• Inclusive and flexible work environment with reasonable accommodation for employees and applicants with disabilities.
• Focus on engineering excellence, collaboration, continuous learning, continuous improvement, and reliable operational performance.