Data Engineering Tech Lead

We are looking for a
Data Engineering Tech Lead
to join our data engineering team. In this role, you will be responsible for leading the design, implementation, and evolution of scalable, cloud-based data solutions, while providing strong technical leadership and guidance to the engineering team.

If you are passionate about cloud data platforms, solution architecture, and mentoring engineers while delivering high-quality data systems in production, this opportunity is for you.

What you will be doing

• Lead the design, implementation, and maintenance of scalable and reliable data solutions on AWS (and Azure where applicable).

• Act as a technical leader for the data engineering team, providing mentorship, guidance, and hands-on support.

• Translate business requirements into technical solutions, break them down into actionable tasks, and distribute work effectively across the team.

• Design robust data architectures considering scalability, performance, security, and cost optimization.

• Build, optimize, and maintain data pipelines, ETL processes, and orchestration workflows using tools such as Apache Airflow, AWS Step Functions, AWS Glue, and Lambda.

• Apply Infrastructure as Code principles using CloudFormation (and Terraform when applicable) to manage and evolve cloud infrastructure.

• Work hands-on with Python and SQL to develop, optimize, and troubleshoot data processing workflows.

• Design efficient data models and optimize query performance across platforms such as Amazon Redshift, PostgreSQL, and MySQL.

• Manage and optimize large-scale datasets, including the use of Iceberg tables for data consistency and performance.

• Ensure production readiness through monitoring, logging, and tracing using AWS services such as CloudWatch, CloudTrail, and AWS X-Ray.

• Collaborate closely with cross-functional teams, including analytics, product, and business stakeholders.

• Produce clear solution designs, technical documentation, and provide training to team members.

• Continuously challenge requirements and propose innovative technical solutions to improve efficiency and performance.

What we are looking for

• Bachelor's or Master's degree in Computer Science, Engineering, or equivalent professional experience.

• 4–5 years of experience in data engineering roles, with at least 2–3 years in a Tech Lead or similar technical leadership position.

• Strong expertise in AWS data and cloud services, including Lambda, Glue, Step Functions, CloudFormation, and CloudWatch.

• Solid experience in solution architecture and designing cloud-native, scalable data systems.

• Strong hands-on skills in Python and SQL.

• Experience working with relational databases such as PostgreSQL, MySQL, and Amazon Redshift.

• Proven experience building and managing ETL pipelines and data integration workflows.

• Familiarity with Iceberg tables and managing large-scale datasets.

• Strong production awareness, with the ability to proactively monitor, troubleshoot, and resolve issues.

• Excellent communication, leadership, and collaboration skills.

• Strong analytical and problem-solving mindset, with the ability to challenge and refine business requirements.

• Full professional proficiency in English (B2 or higher).

Plus (not required but valued)

• Exposure to Azure data services and Azure Databricks.

• Experience with streaming and real-time data technologies such as Kafka and Apache Flink.

• Experience with cloud-native and serverless architectures.

• Familiarity with CI/CD practices for data engineering workflows.

• AWS and/or Azure cloud certifications.

Why join us?

• Take a key technical leadership role in building and evolving modern cloud data platforms.

• Work in a collaborative, technically strong, and supportive team environment.

• Have real influence over architectural decisions and engineering best practices.

• Opportunity to mentor engineers and grow as a technical leader.

• Continuous learning and professional development opportunities.

• A culture that values technical excellence, ownership, and continuous improvement.

Location

Porto, Portugal – Hybrid model (3 days per week on-site)