Key skills
AWSCloudDockerElasticSearchETLGrafanaKafkaKubernetesPythonSparkSQLTableauELTData LakeBIPower BIDatabricksElasticsearchDatadogNew RelicVersion Control
About this role
Role Overview
- Design and implement cloud data architectures, ensuring scalability, security, and high performance;
- Develop, optimize, and monitor data pipelines (ETL/ELT), ensuring efficiency and reliability;
- Build and maintain Data Warehouse and/or Data Lake environments, ensuring data quality, integrity, and governance;
- Optimize data models and SQL queries for continuous performance improvement;
- Create dashboards and executive reports, turning data into strategic insights to support decision-making;
- Automate data ingestion, transformation, and delivery processes;
- Collaborate with cross-functional teams, applying best practices for version control, documentation, and secure development;
- Contribute to the advancement of a data-driven culture and the continuous improvement of implemented solutions.
Requirements
- Python;
- Cloud (preferably AWS stack);
- SQL;
- Visualization tools such as Power BI, Tableau, Google Data Studio, and others;
- Spark;
- ETL tools (Extract, Transform, Load).
- Preferred:
- Kubernetes;
- Monitoring tools (Grafana, New Relic, Datadog, and others);
- Databricks;
- Docker;
- Kafka;
- API development;
- Elasticsearch.
Tech Stack
- AWS
- Cloud
- Docker
- ElasticSearch
- ETL
- Grafana
- Kafka
- Kubernetes
- Python
- Spark
- SQL
- Tableau