{"id":3618989,"url":"https://alion.io/job/manila-recruitment-lead-data-engineer-gcp-remote","title":"Lead Data Engineer (GCP) REMOTE","company":{"id":1582,"name":"Manila Recruitment","domain":"manilarecruitment.com","url":"https://alion.io/company/manila-recruitment","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":75,"open_postings":11,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":44,"computed_at":"2026-11-04T06:34:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["PH"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-02T17:38:18Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-04T17:25:24Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"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.\nLead 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 address immediate business needs while remaining scalable and maintainable.\nEstablish and reinforce engineering standards across Python, SQL, orchestration, testing, documentation, data governance, and monitoring. Leverage AI and automation to reduce repetitive tasks, such as test and documentation generation and early detection of data quality issues, allowing the team to focus on more complex engineering challenges.\nSet the technical direction and quality standards for data engineering. Conduct design and code reviews, share technical knowledge, and support the onboarding, development, and guidance of engineers as the team grows.\nPartner 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.\nRequirements\nAt least 5 years of hands-on experience in data engineering, particularly in designing, building, and maintaining production data pipelines and cloud-based data infrastructure.\nStrong hands-on experience with dbt (Data Build Tool) for data transformation, modelling, and management of analytics workflows.\nSolid experience with Google Cloud Platform (GCP), particularly BigQuery and other relevant data processing and storage services.\nProven experience using Apache Airflow for workflow orchestration, scheduling, monitoring, and managing data pipelines.\nStrong proficiency in Python and SQL, with the ability to develop scalable data solutions and troubleshoot complex technical issues.\nGood understanding of data architecture, data warehousing, ETL/ELT processes, performance optimisation, data quality, monitoring, and governance.\nExperience designing technical solutions, leading complex data engineering projects, and taking ownership of delivery and ongoing system performance.\nAbility to establish engineering standards, conduct code reviews, provide technical guidance, and share knowledge with other engineers.\nFamiliarity with AI-assisted development, automation, or modern engineering practices to improve development productivity, data quality, and operational efficiency.\nStrong problem-solving and decision-making skills, with the ability to balance technical priorities and business requirements and communicate effectively with technical and 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