Analytics Engineer

DoiT International

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

Posted 11/10/2026full-timeRemote • Colombia, MexicoMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in analytics engineering and data modeling, with a strong focus on SQL, dbt, and CI/CD practices. Proficient in building and maintaining data pipelines and models, while effectively collaborating with cross-functional teams to meet business needs.

Highest-signal resume keywords

SQL ProficiencyDbt ExperienceBigQuery KnowledgeData Modeling SkillsCI/CD Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModelingSQLDbtPythonTerraformBigQueryData Pipeline DevelopmentAutomated TestingData AnalysisDebugging

Soft Skills

Clear Written CommunicationCollaborationIndependenceProblem-SolvingStakeholder Engagement

Tools & Technologies

Apache AirflowCloud ComposerFivetranGitDockerKubernetesData Catalog ToolsData Observability ToolsAI Coding ToolsSaaS Source Systems

Industry Keywords

Analytics EngineeringData EngineeringBusiness IntelligenceCI/CD WorkflowsData InfrastructureCloud ResourcesData GovernanceRBAC ImplementationSchema DriftObservability

Tech Stack

Tools & technologies

AirflowApacheAWSAzureBigQueryCloudDockerKubernetesPythonSQLTerraform

About the role

Key responsibilities & impact

Share ownership of the data platform’s engineering, including model changes, the 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, maintain data catalog metadata and documentation
Improve platform reliability through stronger testing standards, observability, and alerting
Support Airflow orchestration and scheduling, including troubleshooting Cloud Composer build failures
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, including complex analytical queries, grain, joins, and layered models
Professional dbt experience, including packages, macros, incremental strategies, snapshots, seeds, CI/CD, staging → intermediate → mart patterns, deferred builds, state comparison, and slim CI
Software engineering discipline with version control, code review, automated testing, and CI/CD
Ability to debug data issues to their root cause and reason about 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 foundational cloud resources
Proven track record of using AI coding tools in daily workflow
Independence in a remote, global team, with clear written communication and documentation discipline
Fluent written and spoken English
Other languages are an advantage
Bonus: hands-on 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 REST API integrations
Bonus: dbt build lifecycle, BigQuery performance tuning, Docker, Kubernetes, SQLFluff/pre-commit, and SaaS source system experience

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