Senior Data Engineer

Role Overview

• Design, build and maintain robust, scalable data pipelines for ingestion, processing and transformation of large volumes of data;
• Develop and optimize data models for analytical systems;
• Implement and manage storage solutions, including data lakes and data warehouses, in cloud environments;
• Ensure data integrity, quality and governance by applying best practices in data management, security and FINOPS;
• Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions;
• Monitor and optimize the performance of pipelines, databases and integration solutions;
• Lead data architecture modernization initiatives using cutting-edge technologies and modern frameworks;
• Act as a technical reference and mentor for junior and mid-level data engineers.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems or related fields;
• Proven experience with data visualization platforms (Tableau, Power BI and/or Looker);
• Track record of leading or actively participating in complex cloud integration and migration projects;
• Cloud computing experience;
• Experience with GCP and its services such as BigQuery, Cloud Composer/Apache Airflow, Dataflow, Pub/Sub, Cloud Run, Cloud Functions, KMS and Secret Manager;
• Knowledge of DataStream, Vertex AI and GitHub;
• Experience with Azure and services such as Azure Data Factory, Azure Synapse Analytics and Azure Data Lake Storage;
• Databases: knowledge of data modeling, relational databases (e.g., Oracle, SQL Server, PostgreSQL) and non-relational databases (e.g., MongoDB, Cassandra);
• Programming languages: proficiency in Python and PySpark (for scripting and automation) and SQL (for data manipulation and querying);
• ETL/ELT: experience building ETL/ELT pipelines for data ingestion and transformation;
• Data Lakes: knowledge of Data Lake architectures, storage and data optimization (e.g., Delta Lake);
• DevOps: experience with CI/CD pipelines and DataOps practices for automating deployments and monitoring data flows;
• Security and governance: understanding of cloud security practices, data encryption and implementation of governance policies;
• Data orchestration: use of tools such as Azure Data Factory and/or Synapse and/or Airflow/Cloud Composer for integration and data movement;
• Performance and optimization: experience with techniques to improve the performance of data pipelines and queries in distributed and non-distributed environments;
• APIs: knowledge of extracting data via RESTful APIs;
• Data engineering certifications on GCP and/or Azure (e.g., Professional Data Engineer, Azure Data Engineer Associate).

Tech Stack

• Airflow
• Apache
• Azure
• BigQuery
• Cassandra
• Cloud
• ETL
• Google Cloud Platform
• MongoDB
• Oracle
• Postgres
• PySpark
• Python
• SQL
• Tableau

Benefits

• Health and Dental Plan – Bradesco – extendable to dependents
• PAE
• Financial assistance offered for dependent children and/or stepchildren with intellectual disabilities
• Pharmacy agreement – discounts up to 85%
• Supplementary pension – FlexPrev Plan – contributions ranging from 1% to 11%, depending on salary
• Life insurance – coverage for all employees from the date of hire, with no employee contribution
• Extended leave – Maternity leave (total of 180 days) and Paternity leave (total of 20 days)
• Meal and/or food allowance – Caju Benefits
• Educational assistance – for dependents up to high school
• TotalPass
• Solar subscription – possibility of a special discount on the electricity bill through participation in a distributed generation plan
• Smiles Corporate Club – discounts up to 50% on offered plans to help you plan your trips; also available for spouse and children 18+
• Length-of-service bonus – an additional salary payment based on tenure, paid at vacation time.