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Tech Stack
Tools & technologiesCloudETLPythonSparkSQL
About the role
Key responsibilities & impact- Serve as the technical reference for building and evolving modern data solutions for the FLOW platform
- Provide technical leadership in the design, implementation, and evolution of data architectures and platforms
- Design, develop, and maintain scalable, resilient, and high-performance data pipelines
- Define standards and best practices for Data Lake, Data Warehouse, and Lakehouse solutions
- Collaborate with different teams to ensure data integrity, quality, security, and availability
- Implement Data Quality and observability practices across pipelines
- Develop and evolve CI/CD pipelines for data processes and ETL/ELT
- Define and implement relational and dimensional data models
- Implement Data Governance practices, including cataloging, lineage, and access control
- Document architectures, workflows, processes, and technical decisions
- Resolve complex technical issues and perform root cause analyses
- Apply FinOps principles to monitor and optimize costs
- Provide technical guidance to the team, contributing to its autonomy and growth
- Use AI to increase productivity and quality throughout the data engineering lifecycle
Requirements
What you’ll need- Solid experience in Data Engineering, working in complex, large-scale environments
- Experience serving as a technical reference, supporting architectural decisions and team evolution
- Advanced knowledge of SQL, Python, and Spark
- Experience with data solutions for Machine Learning, generative AI, or agent-based systems
- Experience with modern data stacks in cloud environments
- Experience building data pipelines and ETL/ELT processes
- Knowledge of data architecture, distributed processing, and integration across different sources
- Experience with CI/CD practices applied to data solutions
- Knowledge of relational and dimensional data modeling
- Ability to evaluate solutions based on scalability, security, performance, cost, and operational sustainability
- Experience applying AI to the software development and data engineering lifecycle
- Degree in Computer Science, Information Technology, Engineering, or a related field
- Preferred: Experience with multiple cloud providers
- Preferred: Experience with Databricks or equivalent platforms
- Preferred: Certifications related to data, cloud, or distributed processing
- Preferred: Experience with Data Lake, Data Warehouse, and Lakehouse architectures
- Preferred: Knowledge of Data Quality, observability, and data reliability
- Preferred: Experience with cataloging, lineage, and governance tools
- Preferred: Knowledge of FinOps applied to the data ecosystem
- Preferred: Experience working on international projects or with international teams
Benefits
Comp & perks- Medical 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 Program (PLR)
- Life insurance
- Continuous learning platform (CI&T University)
- Discount club
- Free online platform dedicated to promoting physical and mental health and well-being
- Pregnancy and responsible parenting course
- Partnerships with online course platforms
- Language learning platform
- Support obtaining disability documentation for people with disabilities
- Dedicated Health and Well-being team
- Inclusion specialists and affinity groups