Senior Data Engineer, GCP

Leega

Senior Data Engineer at Leega driving the evolution of data architecture and pipelines. Leading technical teams and designing scalable data solutions in cloud environments.

Posted 5/27/2026full-timeSão Paulo • 🇧🇷 BrazilSeniorWebsite

Tech Stack

Tools & technologies

AirflowApacheBigQueryCloudDockerETLGoogle Cloud PlatformKafkaKubernetesOraclePySparkPythonSparkSQLTerraform

About the role

Key responsibilities & impact

Lead the design and evolution of data architecture (Data Lake, Data Warehouse, Lakehouse)
Design, develop and optimize high-scale data pipelines (ETL/ELT)
Act as the technical reference for the data engineering team
Work with distributed processing using Databricks (Spark/PySpark)
Define development, testing and deployment best practices (DataOps)
Ensure data governance, quality, security and reliability
Optimize performance and costs in GCP environments
Integrate multiple data sources (batch and streaming)
Support BI, Analytics and Data Science teams in delivering data
Participate in strategic decisions related to data and technology

Requirements

What you’ll need

Minimum 5 years of experience as a Data Engineer
Strong experience with Google Cloud Platform (BigQuery, Dataflow, Cloud Storage, Pub/Sub)
Advanced experience with Databricks and Apache Spark (PySpark)
Experience with Snowflake
Proficiency in Python and SQL
Experience with data modeling (relational, dimensional and Lakehouse)
Experience with pipeline orchestration (Airflow/Cloud Composer or similar)
Experience with code versioning and CI/CD practices
Experience with large-scale data environments
Experience developing scalable solutions
Knowledge of Oracle Cloud (OCI)
Experience with Delta Lake and Lakehouse architecture
Knowledge of infrastructure-as-code (Terraform)
Experience with Docker/Kubernetes
Knowledge of data streaming (Kafka, Pub/Sub)
Certifications (GCP Professional Data Engineer, Databricks)
Experience with observability and monitoring tools
Previous experience in the Insurance and Services sectors
Experience in startups, fintechs, or fast-paced environments

Benefits

Comp & perks

Hybrid work (onsite once every 15 days)
Project duration: 6 months, with the possibility of extension up to 1 year.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data architecturedata pipelinesETLELTDatabricksApache SparkPythonSQLdata modelingpipeline orchestration

Soft Skills

leadershipcommunicationstrategic decision making

Certifications

GCP Professional Data EngineerDatabricks