Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Роль описана чётко и даёт заметную ответственность за промышленную data-платформу, хотя широкий охват инфраструктуры и управления данными может сделать работу интенсивной.
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Широкая зона ответственностиСовременный стекЧёткие обязанностиПоддержка развитияБаланс работы и жизни
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Analytics Engineer (dbt/SQL): Building and operating governed data models, pipelines, and infrastructure for dashboards, financial reporting, and AI analytics across 15+ business domains with an accent on reliability, governance, and automation. Focus on provisioning BigQuery resources with Terraform, extending RBAC, developing Python-based Fivetran connectors, and improving testing, observability, and orchestration.
Location: Remote in Mexico or Colombia as a full-time employee, or in other LATAM locations as a contractor; working hours must overlap meaningfully with US time zones.
Company
hirify.global is a global technology company providing cloud intelligence and multicloud solutions that combine technology with human expertise for more than 4,000 customers.
What you will do
Share ownership of the governed data platform, including model changes, engineering backlog, data-source onboarding, CI/CD maintenance, and infrastructure operations.
Build, test, and maintain data models and pipelines supporting dashboards, finance and investor reporting, and the AI analytics layer across 15+ business domains.
Provision and configure BigQuery datasets, views, GCS buckets, and IAM permissions with Terraform, including ingestion destinations, access controls, and schema drift management.
Own RBAC expansion, data catalog metadata, documentation, testing standards, observability, alerting, and platform reliability.
Support Airflow and dbt scheduling in Cloud Composer and troubleshoot build failures.
Build Python-based Fivetran SDK connectors with pagination, rate limiting, error handling, and automated tests; partner with BI analysts and use AI tooling to accelerate development.
Requirements
3–5 years of experience in analytics engineering, data engineering, or BI engineering, with a track record of delivering dependable data models.
Strong SQL skills, including complex analytical queries, query optimization, grain and join reasoning, and layered data modeling across staging, business logic, and consumption layers.
Professional experience building and maintaining dbt projects, including packages, macros, incremental strategies, snapshots, seeds, CI/CD, staging-to-intermediate-to-mart patterns, deferred builds, state comparison, and slim CI.
Software engineering discipline with version control, code review, automated testing, CI/CD, and a strong drive to automate repetitive manual work.
Ability to debug data issues to their root cause and account for freshness, volume, duplicates, and late-arriving data.
Ability to translate business needs into data requirements, work with non-technical stakeholders including Finance, and challenge unsuitable approaches constructively.
Comfort working across multiple repositories covering transformation, data infrastructure, orchestration, custom connectors, and foundational cloud resources.
Proven daily use of AI coding tools, independence in a remote global team, clear written communication, and disciplined documentation.
Fluent written and spoken English.
Nice to have
Experience with Google BigQuery, Fivetran, Apache Airflow or Cloud Composer, or equivalent AWS/Azure technologies.
Experience with data catalogs or observability tools such as OpenMetadata or Elementary.
Experience with Git-based CI/CD for data projects, Docker image builds, and automated plan/apply workflows.
Experience provisioning BigQuery datasets, IAM bindings, or GCS buckets with Terraform.
Python experience integrating REST APIs, including pagination, rate limiting, and error handling.
Strong understanding of the dbt build lifecycle, Jinja compilation, run/test/snapshot phases, and advanced macros.
BigQuery performance tuning using partitioning, clustering, incremental strategies, and slot and query-cost analysis.
Docker and basic Kubernetes experience, including pods, logs, and deployments.
Experience with SQLFluff, pre-commit frameworks, or custom validation scripts.
Experience modeling data from CRM, support, project management, marketing automation, or ERP platforms.
Knowledge of another language.
Culture & Benefits
Remote work with flexible scheduling that supports work-life balance.
Professional and personal development support.
Full-time employee benefits include unlimited vacation, flexible working options, health insurance, parental leave, and a home office allowance.
Employee stock option plan, professional development stipend, and peer recognition program.
Inclusive, equitable environment focused on entrepreneurship, learning, collaboration, and diversity.
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