Lead Data Engineer, GCP

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

📋 Description

• Take charge of the reliability, scalability, and performance of the core data pipelines and infrastructure within the company.

• Establish technical priorities, identify potential risks, and drive enhancements to ensure that data remains precise, accessible, and reliable as the organization expands.

• Lead the design and execution of intricate data engineering initiatives, from architecture and technical planning through to implementation.

• Make informed technical choices, balance competing priorities, and guarantee that solutions are both scalable and maintainable.

• Create and uphold engineering standards across Python, SQL, orchestration, testing, documentation, data governance, and monitoring.

• Utilize AI and automation to minimize repetitive tasks, including the generation of tests and documentation, as well as the early detection of data quality issues.

• Define the technical direction and quality benchmarks for data engineering.

• Perform design and code reviews, disseminate technical knowledge, and assist in the onboarding, development, and mentorship of engineers.

• Collaborate with Data Science, BI, and business teams to convert data requirements into viable technical solutions.

• Anticipate dependencies, address complex challenges, and enhance the data foundation that supports analytics, machine learning, and business decision-making.

⛳️ Requirements

• A minimum of 5 years of practical experience in data engineering, specifically in the design, construction, and maintenance of production data pipelines and cloud-based data infrastructure.

• Extensive hands-on experience with dbt (Data Build Tool) for data transformation, modeling, and management of analytics workflows.

• Solid experience with Google Cloud Platform (GCP), particularly BigQuery and other relevant data processing and storage services.

• Proven experience utilizing Apache Airflow for workflow orchestration, scheduling, monitoring, and managing data pipelines.

• Strong skills in Python and SQL, with the capability to develop scalable data solutions and resolve complex technical challenges.

• Good comprehension of data architecture, data warehousing, ETL/ELT processes, performance optimization, data quality, monitoring, and governance.

• Experience in designing technical solutions, leading complex data engineering projects, and taking responsibility for delivery and ongoing system performance.

• Ability to establish engineering standards, conduct code reviews, provide technical guidance, and share insights with fellow engineers.

• Familiarity with AI-assisted development, automation, or modern engineering practices aimed at enhancing development productivity, data quality, and operational efficiency.

• Strong problem-solving and decision-making abilities, with the capacity to balance technical priorities and business needs while communicating effectively with both technical and non-technical stakeholders.

🏝️ Benefits

• Comprehensive health insurance coverage.

• Opportunities for professional development and continued education.

• Flexible work hours and remote work options.

• A collaborative and inclusive work environment.

• Competitive salary and performance-based bonuses.