Lead Data Engineer (GCP)
New
M
Manila RecruitmentData engineering
PhilippinesFull-TimeLead
Salary not disclosed
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Job Details
- Experience
- At least 5 years of hands-on experience in data engineering
- Required Skills
- PythonSQLApache AirflowData engineeringBigQuerydbt
Requirements
- Have at least 5 years of hands-on experience in data engineering.
- Have experience designing, building, and maintaining production data pipelines and cloud-based data infrastructure.
- Bring hands-on experience with dbt for data transformation, modelling, and analytics workflows.
- Have experience with Google Cloud Platform, particularly BigQuery and related data processing and storage services.
- Have experience using Apache Airflow for workflow orchestration, scheduling, monitoring, and pipeline management.
- Be proficient in Python and SQL, including developing scalable data solutions and troubleshooting technical issues.
- Understand data architecture, data warehousing, ETL/ELT processes, performance optimisation, data quality, monitoring, and governance.
- Have experience designing technical solutions, leading complex data engineering projects, and owning delivery and ongoing system performance.
- Be able to establish engineering standards, conduct code reviews, provide technical guidance, and share knowledge.
- Be familiar with AI-assisted development, automation, or modern engineering practices.
- Have problem-solving and decision-making skills and be able to balance technical priorities with business requirements.
Responsibilities
- Own the reliability, scalability, and performance of core data pipelines and infrastructure.
- Set technical priorities, identify risks, and drive improvements to data accuracy, accessibility, and dependability.
- Lead complex data engineering initiatives from architecture and technical planning through implementation.
- Establish engineering standards for Python, SQL, orchestration, testing, documentation, data governance, and monitoring.
- Use AI and automation to reduce repetitive tasks and support data quality.
- Conduct design and code reviews, share technical knowledge, and support engineer onboarding and development.
- Partner with Data Science, BI, and business teams to translate data requirements into technical solutions.
- Resolve complex issues and strengthen the data foundation for analytics, machine learning, and business decision-making.
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