Analytics Engineer

DoiT International

. Share ownership of the data platform’s engineering, including model changes, engineering backlog, data source onboarding, CI/CD maintenance, and infrastructure operations .

Posted 10/26/2026full-timeRemote • Mexico, ColombiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in analytics engineering and data modeling, with a strong focus on building and maintaining data pipelines and models using SQL, dbt, and Python. Proficient in cloud data infrastructure management, CI/CD practices, and collaboration with cross-functional teams to deliver reliable data solutions.

Highest-signal resume keywords

SQLData ModelingDbt Project ManagementBigQueryPython

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Analytics EngineeringData EngineeringData Pipeline DevelopmentCI/CD MaintenanceAutomated TestingDebugging Data IssuesData Requirements TranslationSchema Drift ManagementRBAC ImplementationObservability Standards

Soft Skills

Clear Written CommunicationIndependence in Remote TeamsCollaboration with Non-Technical Stakeholders

Tools & Technologies

TerraformFivetranApache AirflowCloud ComposerGitDockerKubernetes

Industry Keywords

Data CatalogData ObservabilityAI Coding ToolsCloud ResourcesSaaS Source Systems

Tech Stack

Tools & technologies

AirflowApacheAWSAzureBigQueryCloudDockerKubernetesPythonSQLTerraform

About the role

Key responsibilities & impact

Share ownership of the data platform’s engineering, including model changes, engineering backlog, data source onboarding, CI/CD maintenance, and infrastructure operations
Build, test, and maintain data models and pipelines powering 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 through Terraform
Onboard ingestion destinations, manage access controls, and handle schema drift on source tables
Own and expand RBAC implementation and maintain data catalog metadata and documentation
Improve platform reliability through stronger testing standards, observability, and alerting
Support Airflow orchestration and scheduling, including troubleshooting dbt build failures in Cloud Composer
Build and maintain Python-based Fivetran SDK connectors with pagination, rate limiting, error handling, and automated tests
Partner with BI analysts to turn ambiguous questions into well-modeled, trustworthy datasets
Raise engineering practices through code review and shared standards
Use modern AI tooling to draft code and accelerate routine work
Report to the Head of Business Intelligence and collaborate with BI analysts, engineers, and business partners

Requirements

What you’ll need

3–5 years in analytics engineering, data engineering, or BI engineering
Strong SQL and data modeling skills
Professional experience building and maintaining dbt projects, including packages, macros, incremental strategies, snapshots, seeds, and CI/CD
Experience with staging → intermediate → mart patterns, deferred builds, state comparison, and slim CI
Software engineering discipline with version control, code review, automated testing, and CI/CD
Strong drive to automate repetitive manual work
Ability to debug data issues to their root cause and consider freshness, volume, duplicates, and late-arriving data
Ability to translate business needs into data requirements and work with non-technical stakeholders, including Finance
Comfort navigating multiple repositories across transformation, data infrastructure, orchestration, custom connectors, and cloud resources
Proven track record of using AI coding tools in daily workflow
Independence in a remote, global team, with clear written communication and discipline to document work
Fluent written and spoken English; other languages are an advantage
Bonus: experience with BigQuery, Fivetran, Apache Airflow/Cloud Composer, or AWS/Azure equivalents
Bonus: data catalog or data observability tooling experience
Bonus: Git-based CI/CD workflows for data projects
Bonus: Terraform for data infrastructure
Bonus: Python for REST API data integration
Bonus: dbt build lifecycle, BigQuery performance tuning, Docker, Kubernetes, SQLFluff/pre-commit, or SaaS source systems

Benefits

Comp & perks

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 to develop skills professionally and personally