Data Engineer – GCP

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

📋 Description

• You will join a team responsible for the design, modeling, and development of an extensive GCP data ecosystem for one of our clients, including Cloud Storage, Cloud Functions, and BigQuery.

• Your involvement will span the entire process, beginning with the collection, analysis, modeling, and documentation of business and technical requirements, which will include direct interaction with clients.

• You will model data from various sources and technologies, troubleshoot, and support complex, high-impact issues to deliver new features and functionalities.

• Your role will entail designing and optimizing data storage architectures, such as data lakes, data warehouses, or distributed file systems, implementing techniques like partitioning, compression, or indexing to enhance data storage and retrieval. You will also identify and resolve bottlenecks, fine-tune queries, and apply caching strategies to improve data retrieval speed and overall system efficiency.

• You will be responsible for identifying and resolving issues related to data processing, storage, or infrastructure. This includes monitoring system performance, detecting anomalies, and conducting root cause analysis to ensure seamless data operations.

• Additionally, you will train and mentor junior data engineers, providing guidance and facilitating knowledge transfer.

⛳️ Requirements

• A minimum of 4 years of experience as a Data Engineer with expertise in GCP cloud-based infrastructure and systems.

• Profound knowledge of the Google Cloud Platform and cloud computing services.

• Significant experience in designing, building, and deploying data pipelines in the cloud to ingest data from various sources, including databases, APIs, and streaming platforms.

• Proficiency in database management systems, including SQL (BigQuery is essential) and NoSQL. The candidate should be capable of designing, configuring, and managing databases for optimal performance and reliability.

• Strong programming skills in SQL, Python, and other scripting languages.

• Expertise in data modeling techniques and database optimization, with necessary knowledge of query optimization, indexing, and performance tuning for efficient data retrieval and processing.

• Familiarity with at least one orchestration and scheduling tool (Airflow is required).

• Experience with data integration tools and techniques, such as ETL and ELT, with the ability to integrate data from multiple sources and transform it for analysis.

• Knowledge of modern data transformation tools (e.g., DBT, Dataform).

• Excellent communication skills to effectively collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, with the ability to convey technical concepts to non-technical stakeholders clearly and concisely.

• Capacity to actively participate in or lead discussions with clients to identify and evaluate tangible and ambitious opportunities for improvement.

• Familiarity with tools such as Git, Jira, Confluence, etc.

• Willingness to learn new technologies and solutions.

• Experience in a multinational environment and with distributed teams.

• Good to have:

• Certifications in big data technologies or cloud platforms.

• Experience with BI solutions (e.g., Looker, Power BI, Tableau).

• Familiarity with ETL tools, such as Talend or Alteryx.

• Experience with Apache Spark, particularly in a GCP environment.

• Experience with Databricks.

• Experience with Azure cloud-based infrastructure and systems.

🏝️ Benefits

• Competitive salary and performance bonuses.

• Opportunities for professional development and training.

• Flexible working hours and remote work options.

• Access to cutting-edge technology and tools.

• Collaborative and inclusive work environment.