Descrição da Função

Were hiring Technical Lead Data Observability & Quality

Location Lisbon | Hybrid model (3 days on-site)

Sector Data Platforms & Analytics | Strategic role in Data Quality and Monitoring

Are you passionate about data integrity and eager to lead the implementation of observability solutions on large-scale data platforms? Were looking for a Technical Lead Data Observability & Quality to drive the rollout, management and continuous improvement of a cutting-edge data monitoring tool within an international data ecosystem.

Your main responsibilities

• Define and apply best practices for data quality & integrity measurement across the platform
• Deploy and maintain data monitors using a code-as-infrastructure approach
• Lead a Data Observability & Quality community alongside the Product Owner
• Provide technical support and coaching to user teams (BI, Data Science, Business Projects)
• Plan and deliver product features, manage backlogs and documentation using Jira
• Oversee platform performance (KPIs, availability, FinOps) and manage Level 2/3 support escalations
• Coordinate platform enhancements, roadmap implementation and process governance
• Collaborate with AWS/Snowflake technical leads, architects and platform delivery teams

What were looking for

• Minimum 3 years of experience as a BI or Data Engineer with solid Data Quality expertise
• Proficiency in SQL (mandatory), knowledge of Snowflake and dbt (nice to have)
• Understanding of Data Observability principles and tools (Sifflet or similar)
• Experience with Agile tools like Jira/Confluence
• Strong experience in monitoring, dashboards, KPIs and audit processes
• Comfortable working across tech teams and business units

Soft skills that make the difference

• Analytical mindset and attention to detail
• Autonomy and proactive approach
• Excellent communication skills
• Team spirit and ability to coordinate communities

Want to lead data quality initiatives in a high-impact global project?

Apply now and help shape the future of trusted data in a complex and dynamic data environment.