{"id":1217976,"url":"https://alion.io/job/maya-senior-analytics-engineer","title":"Senior Analytics Engineer","company":{"id":50036,"name":"Maya","domain":"maya.ph","url":"https://alion.io/company/maya-ph","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Metro Gate Indang, 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creating training data as well as real-time inference features.\nImplement data quality and integrity checks and ensure the quality and availability of data sources in accordance with their SLAs.\nAlign with Data Engineering and Data Governance team to achieve maturity in the data.\nCreate and maintain software packages for use by our Data Scientists to help improve their model development workflow.\nBuild CI/CD pipelines to improve time to deploy data pipelines and proactively catch issues before they hit production\nProvide guidance on best practices for code and architecture of data pipelines and do code and architecture reviews to ensure adherence to best practices\nCommunicate technical architecture and solutions, as well as explain the competitive advantage of various technologies to a broad audience\nCreate and maintain architecture and systems documentation\nBuild the infrastructure and tooling that enable self-serve pipelines for other Analytics Engineers, and mentor them on best practices\nREQUIRED QUALIFICATIONS\nWith at least a bachelor's degree in any quantitative discipline (i.e. Computer Science, Math, Physics, etc)\nAt least 4 years of experience building and maintaining production ETL/ELT pipelines, including at least 1 year in a technical leadership or mentoring capacity (e.g., leading design reviews, setting team standards, onboarding junior engineers)\nAt least 4 years of experience managing stakeholders across technical and non-technical audiences\nDemonstrated experience usingdbt for data transformation in a production environment\nDISPLAYED SKILL MASTERY\nHigh proficiency in cloud data warehouses (Redshift, Databricks, etc.) and SQL/Spark for data manipulation\nHigh proficiency in designing, developing, and monitoring ETL/ELT pipelines\nAt least 5 years working with AWS or another cloud provider (GCP, Azure)\nModerate experience (at least 3 years) with common data science tools, packages (Pandas, SKLearn), and concepts\nProven experience using dbt for ETL\nStrong programming skills (Python, R, or Bash for pipeline development)\nExperience designing data models (dimensional modeling, star/snowflake schema)\nExperience with orchestration tools (Airflow, Dagster, or similar)\nExperience mentoring junior engineers and setting technical standards/best practices\nExperience working in Agile/DevOps/TDD environments\nStrong stakeholder communication skills across technical levels","description_format":"text","description_chars":2939,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":4,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Payment Processing & Gateways","Digital Banks & 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