Hybrid Data Engineering Manager

Posted last week

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About the role

  • Engineering Manager leading analytics engineering team at Teya, a flexible payment service provider in Portugal. Drive data warehouse design and enhance business analytics capabilities.

Responsibilities

  • Lead, coach, and grow a high-performing analytics engineering team
  • Own the technical direction around data warehouse design, modelling, and modernisation
  • Ensure best practices in dimensional modelling, data quality, testing, and documentation
  • Collaborate with embedded analytics teams to build and maintain trusted, scalable data products
  • Plan, prioritise, and deliver projects in alignment with business goals and timelines
  • Review and contribute to technical designs, DBT models, SQL logic, and pipeline architectures
  • Introduce and enable AI-driven analytics and automation across data products where appropriate
  • Drive Snowflake cost optimisation and ensure efficient resource usage across environments
  • Improve automation, data lineage, observability, and self-service capabilities
  • Work closely with Data Engineering and Platform teams on roadmap alignment and resource planning
  • Foster a culture of continuous improvement, knowledge sharing, and operational excellence

Requirements

  • Strong technical background with hands-on experience in data warehouse design and development
  • 5+ years in data engineering, analytics engineering, or equivalent
  • 2+ years leading or managing technical teams
  • Deep understanding of dimensional modelling and data warehousing principles (star/snowflake schemas, slowly changing dimensions, etc.)
  • Expert SQL and strong experience with DBT and modern ELT pipelines
  • Experience with Snowflake and AWS services
  • Experience managing and delivering complex data or analytics projects
  • Ability to guide architectural decisions and uphold engineering standards
  • Strong communication skills and stakeholder management experience
  • Nice to Have
  • Experience with Snowflake and AWS services
  • Familiarity with data quality/observability tooling and governance practices
  • Python experience for pipeline development or automation
  • Exposure to AI/ML–assisted analytics or productivity tooling

Benefits

  • We trust you, so we offer flexible working hours, as long it suits both you and your team;
  • Health Insurance;
  • Meal Allowance;
  • 25 days of Annual leave (+ Bank holidays);
  • Public Transportation Card;
  • Frequent team events & activities in the office and outside;
  • Office snacks every day;
  • Friendly, comfortable and informal office environment.

Job title

Data Engineering Manager

Job type

Experience level

Mid levelSenior

Salary

Not specified

Degree requirement

Bachelor's Degree

Tech skills

Location requirements

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