Senior Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, develop, and maintain robust, scalable, and efficient data pipelines within a GCP environment, emphasizing BigQuery.

• Implement and oversee data ingestion processes from ERP systems, files, and APIs.

• Create, enhance, and document dimensional data models and analytical solutions within a Lakehouse architecture.

• Orchestrate and monitor ETL/ELT processes utilizing Informatica Cloud.

• Collaborate with Analytics, Data Science, and Product teams to facilitate data-driven analyses and solutions.

• Ensure data quality, governance, and security throughout the entire data lifecycle.

• Employ data engineering best practices, including version control, automation, and testing.

• Optimize queries and enhance the performance of analytical environments.

• Manage requests and set expectations with a variety of stakeholders, including leadership and business teams.

• Provide technical insights contributing to the advancement of data practices, processes, and architecture.

⛳️ Requirements

• Strong experience with Google Cloud Platform (GCP).

• Advanced expertise in BigQuery.

• Experience with Informatica Cloud for orchestrating data pipelines.

• Understanding of Lakehouse-based analytical architectures.

• Experience in dimensional modeling and data warehousing.

• Experience in ingesting and integrating data from ERPs, files, and APIs.

• Advanced SQL skills, including best practices for query optimization and performance tuning.

• Experience with data governance, quality, and security.

• Proven experience working on complex projects and collaborating with various teams and stakeholders.

• Familiarity with Microsoft Analysis Services (a plus).

• Experience with graph databases, particularly Neo4j (a plus).

• Background in multi-cloud or hybrid environments (a plus).

• Experience with real-time data integration and processing (streaming) (a plus).

• Knowledge of Agile methodologies (a plus).

• Experience in applying DevOps practices within data engineering (a plus).

• Excellent communication skills for both technical and non-technical audiences.

• Ability to translate business requirements into practical, scalable solutions.

• Capacity to influence decisions and cultivate trusted relationships with stakeholders.

• Analytical and problem-solving mindset.

🏝️ Benefits

• Develop skills and expertise through challenging projects and business scenarios.

• Engage in collaboration, knowledge sharing, and continuous improvement.

• Connect with colleagues from around the globe and share insights.

• Participate in high-quality projects.

• Experience a multicultural and diverse work environment.

• Work on projects that involve AI, data, and business transformation.