Analytics Engineer

doitintl; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Flexible working options

Health coverage

Paid leave

Equity plan

Home office support

Professional development funding

Peer recognition

Job summary

doitintl is seeking a hands-on analytics engineer to build and operate a governed analytics data platform used across business functions. You will work on data modeling, infrastructure, governance, reliability, and source integrations, coordinating with analysts and stakeholders to deliver trusted datasets for reporting and analytics.

This remote role supports Mexico, Colombia, or LATAM on contract with meaningful overlap with US working hours.

Qualifications

• Experience delivering data models others rely on.
• Strong SQL and data modeling skills with careful grain and join choices.
• Proficient in building and maintaining dbt projects including tests, macros, incremental models and CI workflows.
• Habits of software engineering: version control, code reviews, automated testing and safe deployment.

Responsibilities

• Maintain the analytics platform backlog and onboard data sources from ingestion to certified datasets.
• Build, test, and maintain data pipelines for dashboards and reporting across domains.
• Provision and manage data warehouse resources, storage, and access controls via infrastructure as code.
• Extend role-based data access, maintain catalog metadata and documentation, and govern growth.
• Improve reliability through testing, monitoring, alerting, and troubleshooting scheduled transformations.
• Develop Python connectors for sources lacking ready-made integrations and translate business questions into well-modeled datasets.

Skills

SQL

Data modeling

dbt

Version control

CI/CD

Data quality

Stakeholder collaboration

Tools

dbt

Terraform

Airflow

Kubernetes

Job description

Role overview

Build and operate a governed analytics data platform used across business functions. This hands‑on engineering role spans data modeling, infrastructure, governance, reliability, and source integrations, partnering with analysts and business stakeholders to deliver trusted datasets for reporting and analytics. The position is remote in Mexico or Colombia for employees, or elsewhere in Latin America on a contract basis, with meaningful overlap with US working hours.

Responsibilities

• Maintain the platform engineering backlog, onboard data sources from ingestion through certified datasets, and support infrastructure and deployment workflows.
• Build, test, and maintain analytical models and pipelines for dashboards, financial reporting, and analytics across business domains.
• Provision and manage data warehouse resources, storage, and access controls through infrastructure as code; address source schema changes.
• Extend role-based data access, maintain catalog metadata and documentation, and keep governance practices current as users and domains grow.
• Improve reliability through testing, monitoring, alerting, and troubleshooting scheduled transformation runs.
• Develop and maintain Python connectors for sources without a ready‑made integration, and work with analysts to turn business questions into well‑modeled datasets.

Requirements

• Around 3–5 years in analytics engineering, data engineering, or BI engineering, delivering data models others rely on.
• Strong SQL and data modeling skills, including query optimization, sound grain and join choices, and layered model design.
• Professional experience building and maintaining dbt projects, including tests, macros, incremental models, snapshots, and CI workflows.
• Software engineering habits such as version control, code review, automated testing, and safe deployment; a drive to automate repetitive work.
• Ability to investigate data quality and pipeline issues, including freshness, duplicates, volume changes, and late‑arriving records.
• Skill translating business needs into data requirements and collaborating constructively with nontechnical partners.

Nice to have

• Experience with Terraform for warehouse or cloud resources, Python REST API integrations, data catalogs or observability tools, and warehouse performance tuning.
• Familiarity with Airflow scheduling, containerized builds, Kubernetes basics, SQL linting, and data from CRM, support, marketing, or finance systems.

Benefits and work setup

• Full‑time employee benefits include flexible working options, health coverage, paid leave, an equity plan, home office support, professional development funding, and peer recognition.