Senior Data Engineer, GCP

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🕒 May 27

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Leega

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2010

🔌 API

🤖 Artificial Intelligence

API • Artificial Intelligence • Cloud Solutions

Leega is a leading technology solutions provider in Latin America, specializing in data analytics and cloud solutions. As the first company in the region certified by Google Cloud for Data Analytics, Leega offers a range of services including application development, machine learning, and risk management analytics. The firm partners with major cloud services such as AWS and Microsoft Azure to help businesses enhance their data management and transition effectively to the cloud, ultimately driving digital transformation and innovation.

📋 Description

• 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

• 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

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