Data Engineer Manager

Accountabilities:

• • Lead the technical design, implementation, and evolution of scalable data architectures and platforms across complex environments.
  • Design, develop, and maintain high-performance, resilient data pipelines and ETL/ELT processes supporting large-scale data workloads.
  • Define architecture standards and best practices for Data Lake, Data Warehouse, and Lakehouse environments.
  • Work with different teams to ensure data integrity, quality, security, availability, and operational reliability.
  • Implement Data Quality, observability, and reliability practices across data pipelines and platforms.
  • Develop and evolve CI/CD pipelines and engineering practices for data processing and ETL/ELT solutions.
  • Define and implement relational and dimensional data models aligned with analytical and operational requirements.
  • Establish Data Governance practices, including data cataloging, lineage, access controls, and documentation.
  • Document architectures, data flows, processes, technical decisions, and relevant engineering standards.
  • Troubleshoot complex technical issues, conduct root-cause analyses, and drive sustainable solutions.
  • Apply FinOps principles to monitor, manage, and optimize the costs associated with data solutions.
  • Act as a technical reference for the engineering team, supporting technical decisions, knowledge sharing, autonomy, and professional development.
  • Leverage AI throughout the data engineering and software development lifecycle to improve productivity, quality, and delivery efficiency.

  Requirements:

  • Degree in Computer Science, Information Technology, Engineering, or a related field.
  • Strong professional experience in Data Engineering, ideally within complex, large-scale environments.
  • Experience acting as a technical reference, contributing to architectural decisions and supporting the evolution of engineering teams.
  • Advanced knowledge of SQL, Python, and Spark.
  • Experience developing data solutions for Machine Learning, Generative AI, or agent-based systems.
  • Experience working with modern data stacks in cloud environments.
  • Strong background in data pipelines, ETL/ELT processes, distributed data processing, and integration across multiple data sources.
  • Solid understanding of data architecture, scalability, security, performance, operational reliability, and cost optimization.
  • Experience applying CI/CD practices to data engineering solutions.
  • Knowledge of relational and dimensional data modeling.
  • Experience using AI within software development and data engineering workflows.
  • Ability to evaluate technical solutions from multiple perspectives, including scalability, security, performance, cost, and long-term sustainability.
  • Experience with multiple cloud providers is a plus.
  • Experience with Databricks or equivalent data platforms is a plus.
  • Certifications related to data, cloud, or distributed processing are a plus.
  • Knowledge of Data Lake, Data Warehouse, and Lakehouse architectures is a plus.
  • Experience with Data Quality, observability, data reliability, cataloging, lineage, and governance tools is a plus.
  • Knowledge of FinOps applied to data ecosystems is a plus.
  • Experience working with international projects or distributed teams is a plus.

  Benefits:

  • Health and dental insurance.
  • Meal and food allowances.
  • Childcare assistance.
  • Extended parental leave.
  • Partnerships with gyms and health and wellness professionals through Wellhub (Gympass) and TotalPass.
  • Profit Sharing and Results (PLR).
  • Life insurance.
  • Continuous learning platform with access to professional development resources.
  • Discounts through partner programs.
  • Free online platform focused on physical health, mental health, and overall well-being.
  • Pregnancy and responsible parenthood courses and support.
  • Partnerships with online learning platforms.
  • Access to language learning platforms.
  • Remote work environment.
  • Additional benefits according to the applicable employment and company policies.