Lead Data Engineer, GCP

Job not on LinkedIn

🔥 0 minutes ago

🇵🇭 Philippines – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 25%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Manila Recruitment

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2010

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Manila Recruitment is a leading recruitment agency based in the Philippines, specializing in innovative talent sourcing and headhunting services. The agency provides a wide range of recruitment solutions including executive search, IT recruitment, offshore staffing solutions, remote staffing, and more. With a focus on understanding clients' strategic business objectives, Manila Recruitment offers tailored recruitment strategies for multinationals, corporations, and start-ups entering the Filipino market. The firm prides itself on a process-driven approach, offering comprehensive candidate guarantees and a database of over 250,000 candidates. Certified headhunters at Manila Recruitment are dedicated to passive candidate sourcing, ensuring quality hires that align with company culture and requirements.

📋 Description

• Own the reliability, scalability, and performance of the company's core data pipelines and infrastructure. • Set technical priorities, identify risks, and drive improvements to ensure data remains accurate, accessible, and dependable as the business grows. • Lead the design and delivery of complex data engineering initiatives from architecture and technical planning through implementation. • Make sound technical decisions, balance competing priorities, and ensure solutions are scalable and maintainable. • Establish and reinforce engineering standards across Python, SQL, orchestration, testing, documentation, data governance, and monitoring. • Leverage AI and automation to reduce repetitive tasks, including test and documentation generation and early detection of data quality issues. • Set technical direction and quality standards for data engineering. • Conduct design and code reviews, share technical knowledge, and support onboarding, development, and guidance of engineers. • Partner with Data Science, BI, and business teams to translate data requirements into practical technical solutions. • Anticipate dependencies, resolve complex issues, and strengthen the data foundation supporting analytics, machine learning, and business decision-making.

🎯 Requirements

• At least 5 years of hands-on experience in data engineering, particularly in designing, building, and maintaining production data pipelines and cloud-based data infrastructure. • Strong hands-on experience with dbt (Data Build Tool) for data transformation, modelling, and management of analytics workflows. • Solid experience with Google Cloud Platform (GCP), particularly BigQuery and other relevant data processing and storage services. • Proven experience using Apache Airflow for workflow orchestration, scheduling, monitoring, and managing data pipelines. • Strong proficiency in Python and SQL, with the ability to develop scalable data solutions and troubleshoot complex technical issues. • Good understanding of data architecture, data warehousing, ETL/ELT processes, performance optimisation, data quality, monitoring, and governance. • Experience designing technical solutions, leading complex data engineering projects, and taking ownership of delivery and ongoing system performance. • Ability to establish engineering standards, conduct code reviews, provide technical guidance, and share knowledge with other engineers. • Familiarity with AI-assisted development, automation, or modern engineering practices to improve development productivity, data quality, and operational efficiency. • Strong problem-solving and decision-making skills, with the ability to balance technical priorities and business requirements and communicate effectively with technical and nontechnical stakeholders.

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