Analytics Engineer

This is a fully remote position, open to applicants in Mexico, +1 more country.

📋 Description

• Take shared responsibility for the engineering aspects of the data platform, which includes model modifications, managing the engineering backlog, onboarding data sources, maintaining CI/CD, and overseeing infrastructure operations.

• Design, test, and sustain data models and pipelines that power dashboards, finance and investor reports, as well as the AI analytics layer across more than 15 business domains.

• Set up and configure BigQuery datasets, views, Google Cloud Storage (GCS) buckets, and IAM permissions using Terraform.

• Facilitate the onboarding of ingestion destinations, manage access controls, and address schema drift on source tables.

• Oversee and enhance Role-Based Access Control (RBAC) implementation, while maintaining the data catalog metadata and documentation.

• Enhance platform reliability by implementing stronger testing standards, observability, and alerting mechanisms.

• Support Airflow orchestration and scheduling, including resolving dbt build failures within Cloud Composer.

• Develop and maintain Python-based Fivetran SDK connectors that include pagination, rate limiting, error handling, and automated testing.

• Collaborate with BI analysts to convert ambiguous queries into well-structured, reliable datasets.

• Elevate engineering practices through code reviews and adherence to shared standards.

• Leverage modern AI tools to draft code and expedite routine tasks.

• Report directly to the Head of Business Intelligence and work closely with BI analysts, engineers, and business stakeholders.

⛳️ Requirements

• 3 to 5 years of experience in analytics engineering, data engineering, or BI engineering.

• Proficient in SQL and data modeling.

• Professional experience in building and maintaining dbt projects, including packages, macros, incremental strategies, snapshots, seeds, and CI/CD processes.

• Familiarity with staging, intermediate, and mart patterns, deferred builds, state comparison, and slim CI methodologies.

• Software engineering discipline, including version control, code review, automated testing, and CI/CD.

• Strong motivation to automate repetitive manual tasks.

• Capability to troubleshoot data issues to their root causes, considering freshness, volume, duplicates, and late-arriving data.

• Ability to convert business needs into data requirements and engage with non-technical stakeholders, including those in Finance.

• Comfortable navigating multiple repositories across transformation, data infrastructure, orchestration, custom connectors, and cloud resources.

• Proven experience in utilizing AI coding tools within daily workflows.

• Self-sufficient in a remote global team environment, with strong written communication skills and a commitment to documenting work.

• Proficient in written and spoken English; additional languages are a plus.

• Bonus: Experience with BigQuery, Fivetran, Apache Airflow/Cloud Composer, or equivalents in AWS/Azure.

• Bonus: Experience with data cataloging or data observability tools.

• Bonus: Familiarity with Git-based CI/CD workflows for data projects.

• Bonus: Proficient in Terraform for data infrastructure.

• Bonus: Knowledge of Python for REST API data integration.

• Bonus: Understanding of the dbt build lifecycle, BigQuery performance tuning, Docker, Kubernetes, SQLFluff/pre-commit, or SaaS source systems.

🏝️ Benefits

• Unlimited Vacation

• Flexible Working Options

• Health Insurance

• Parental Leave

• Employee Stock Option Plan

• Home Office Allowance

• Professional Development Stipend

• Peer Recognition Program

• Remote work and schedule flexibility

• Opportunities for both professional and personal skill development