• Design and structure the build of a data platform on AWS that meets the needs of internal stakeholders; • Identify the best solutions to optimize the architecture of our data platform; • Ensure data observability, quality, and reliability for our internal and external stakeholders; • Automate pipeline testing processes for onboarding new data sources, integrated with CI/CD; • Execute the data platform adoption plan together with the teams responsible for data governance; • Collaborate with data scientists and software engineers to enable an integrated data flow.

• Work closely with Full Stack developers, other data engineers, and data scientists to provide production-ready data via APIs or ML models. • Implement the architecture of a data platform (Data Lakehouse) and support the data lifecycle, ensuring integrity at every stage of the pipeline. • Configure and optimize Apache Iceberg tables to support ACID transactions, schema evolution, and hidden partitioning, ensuring consistency and concurrent reads. • Build automated Airflow workflows with preprocessing and metadata extraction following a factory pattern. • Implement data contracts and automated pipeline quality tests to ensure the Lakehouse is a reliable source of truth for the company’s products. • Apply DevOps best practices to ensure the platform infrastructure is provisioned using Terraform.

Role Description We are looking for a Data Engineer to join our team. Your responsibilities will include: - Develop, maintain, and optimize data pipelines for data ingestion, transformation, and availability; - Implement and manage ETL/ELT processes, ensuring data quality, integrity, and consistency; - Collect, organize, and structure data from different sources (databases, APIs, files, etc.); - Perform relational and dimensional data modeling to support analytical and BI needs; - Work with relational and analytical databases, optimizing queries and performance; - Support the development and maintenance of Data Warehouses and Data Marts; - Create, enhance, and maintain existing dashboards and reports, ensuring performance, usability, and alignment with business rules; - Support and enhance BI tools such as Tableau, Looker Studio, and Apache Superset; - Develop automations and routines for data processing and control; - Monitor pipelines and data flows, identifying failures and proposing continuous improvements; - Document processes, architectures, pipelines, dashboards, and business rules; - Work closely with data analysts, data scientists, and stakeholders to ensure accessible, reliable, and well-presented data; - Participate in data projects end-to-end, including delivery, maintenance, and evolution of solutions; - Support technical and functional presentations for both technical and non-technical audiences. Qualifications - Business English (minimum B2 Level); - 3 to 5 years of experience as a Data Analyst, Data Engineer, or similar roles, focused on Data Engineering and BI (mid-level); - Experience with relational and/or analytical databases such as Amazon Redshift, MySQL, SQL Server, Oracle, or PostgreSQL; - Strong SQL skills and experience with Python for building pipelines, automations, and supporting analysis; - Solid knowledge of database concepts: ER models (conceptual and logical); - Relational and dimensional data modeling; - Table structures, data types, and formats (CSV, JSON, Parquet); - DBMS knowledge; - Hands-on experience with ETL/ELT processes and tools; - Experience with BI tools, including Apache Superset, Tableau, Power BI, or Looker Studio, focused on dashboard creation and maintenance; - Experience with version control (Git); - Good communication, organization, and teamwork skills; - Analytical mindset with a focus on problem-solving and continuous improvement; - Bachelor’s degree in Information Systems, Computer Science, Software Engineering, Computer Engineering, or related fields; Requirements - Experience or knowledge in Cloud Computing (AWS, Azure, GCP, or OCI); - Experience with cloud data services (Data Lake, Data Warehouse, orchestration); - Experience with pipeline orchestration tools (Airflow, Prefect); - Knowledge of modern data architectures (Data Lake, Lakehouse); - Experience with agile methodologies (Scrum, Kanban); - Basic knowledge of DataOps and data observability best practices. Benefits - A salary adequate to your experience, with 100% transparency; - Meal Voucher worth R$800,00 a month, with options for Food Voucher; - Transportation vouchers for commuting; - Partnerships Club with agreements and discounts for educational institutions and banking benefits; - Referral Program offering up to R$600 per person who stays with us for more than 6 months; - Remote or hybrid work model; - Working hours from Monday to Friday, 9am to 6pm; - Time bank for extra hours worked; - Additional paid holiday on your birthday and work anniversary; - Special leave policies for personal events; - Medical and Dental Assistance along with Group Life Insurance; - Access to the iFeel app for emotional support; - ApoioPass for professional support in various areas; - Gympass for you and 3 other people; - Pet Plan extending care to your pet; - Payroll loan services, eligible after 6 months of employment.

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