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Senior Data Engineer
INDT - Instituto de Desenvolvimento Tecnológico. Design, develop, and implement scalable, efficient data pipelines, including data ingestion, transformation, and delivery .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates extensive experience in Data Engineering with a focus on developing and maintaining end-to-end data pipelines, utilizing tools such as Snowflake, dbt, and Apache Airflow. Proficient in Python and SQL for data transformation, optimization, and ensuring data quality and integrity.
Highest-signal resume keywords
Data EngineeringSnowflakeApache AirflowPythonSQL
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DevelopmentData TransformationData Quality AssuranceETL/ELT ProcessesData ModelingPerformance OptimizationCloud Resource ManagementVersion ControlDataOpsAPI Integration
Soft Skills
Analytical ThinkingProblem-SolvingAttention to DetailClear CommunicationCollaboration
Tools & Technologies
Google Cloud PlatformGitAzure DevOpsApache SparkDbt
Industry Keywords
Data LakesData WarehousesPipeline OrchestrationDAG DevelopmentData Governance
Tech Stack
Tools & technologiesAirflowApacheAzureCloudETLGoogle Cloud PlatformPythonSnowflakeSparkSQL
About the role
Key responsibilities & impact- Design, develop, and implement scalable, efficient data pipelines, including data ingestion, transformation, and delivery
- Maintain and enhance existing pipelines, ensuring the stability, reliability, and availability of information
- Develop and integrate new data sources into the platform
- Monitor pipelines, identify failures, bottlenecks, and inconsistencies, and proactively resolve incidents
- Analyze and optimize pipeline and query performance
- Monitor and optimize cloud resource consumption, balancing performance, quality, and costs
- Implement tests, validations, and controls to ensure data quality and integrity
- Work with code versioning, change control, and delivery management
- Create and maintain technical documentation covering pipelines, data sources, transformation rules, and architecture
- Support business users in accessing, understanding, and using data
- Partner with Business, Analytics, Data Science, and Engineering teams to build scalable solutions
Requirements
What you’ll need- Extensive experience in Data Engineering, including the development and maintenance of end-to-end pipelines
- Knowledge of Snowflake, including data modeling, administration, and performance optimization
- Experience with dbt, including model development, testing, and documentation
- Experience with Apache Airflow / Composer, pipeline orchestration, and DAG development
- Knowledge of Apache Spark / Dataproc, distributed processing, and optimization
- Experience with Google Cloud Platform (GCP), particularly Google Cloud Storage
- Advanced proficiency in Python applied to Data Engineering, automation, ETL, and API integration
- Advanced SQL knowledge, including complex queries, data transformation, and query optimization
- Experience with Git, Azure DevOps, version control, and CI/CD practices
- Knowledge of data modeling, Data Lakes, Data Warehouses, and ETL/ELT processes
- Experience with DataOps, data quality, and data governance practices
- Residence in São Paulo required
- Ability to anticipate issues, identify risks, and propose solutions
- Strong attention to detail and commitment to data integrity and reliability
- Clear and concise communication
- Strong organization, discipline, and ability to manage priorities
- Analytical thinking and problem-solving skills
- Ownership mindset and autonomy
- Results-oriented approach
- Collaboration and teamwork
- Adaptability and continuous learning
Benefits
Comp & perks- Collaborative work environment
- Learning and growth opportunities
- Inspiring leaders
- Freedom to propose and develop innovative projects
- Autonomy and ownership
- Hybrid work option, with on-site attendance at the client’s location once a week