Data Engineer

This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client’s time zone.

Our client is an AI company focused on forecasting and attribution intelligence products. The Data Engineering team builds and maintains data pipelines that support analytics, customer onboarding, reporting, forecasting, and AI-driven use cases.

ROLE OVERVIEW

The Data Engineer will help build and maintain reliable, analytics-ready data pipelines that power AI-driven forecasting and attribution intelligence products.

This is a hands-on contract role focused on execution, quality, and collaboration across Analytics, Data Science, and Product teams. The Contract Data Engineer will work within a modern analytics engineering stack centered on Python, dbt, and Dagster, primarily supporting customer onboarding and reporting workflows.

LOCATION

Fully Remote | 9:00 AM - 5:00 PM EST

KEY RESPONSIBILITIES

DATA PIPELINE DEVELOPMENT

• Build and maintain scalable, fault-tolerant ELT pipelines using Python.

• Model clean, analytics-ready datasets for BI, forecasting, and ML feature consumption.

• Contribute to the refactoring and improvement of existing data workflows as product needs evolve.

DBT DEVELOPMENT

• Develop and optimize dbt models.

• Build and maintain dbt tests and documentation.

• Follow analytics engineering best practices.

WORKFLOW ORCHESTRATION & MONITORING

• Orchestrate and monitor workflows using Dagster.

• Monitor pipeline health using observability tools and metrics.

• Troubleshoot pipeline failures, performance issues, and data inconsistencies.

DATA QUALITY

• Implement and maintain data quality checks.

• Develop and maintain testing strategies.

• Follow established team standards for SLAs, code quality, and deployments.

CROSS-FUNCTIONAL COLLABORATION

• Collaborate with Data Scientists to support forecasting and AI-driven use cases.

• Work cross-functionally with Product, Analytics, and Data Science teams.

• Work closely with clients to solve data issues.

QUALIFICATIONS

EXPERIENCE

• 3+ years of professional experience in data engineering or analytics engineering.

• Hands-on experience with dbt Core or Cloud.

• Hands-on experience with Dagster or similar orchestration tools.

• Experience with cloud data warehouses such as Snowflake, BigQuery, or Redshift.

• Experience working cross-functionally with Product, Analytics, or Data Science teams.

• Experience supporting machine learning or forecasting pipelines is a plus.

• Experience with retail, supply chain, or time-series data is a plus.

• Experience with data observability or quality tooling is a plus.

• Startup or fast-paced product environment experience is a plus.

SKILLS

• Strong proficiency in Python, including tools such as pandas, SQLAlchemy, and psycopg2.

• Advanced SQL skills, including CTEs, window functions, and query optimization.

• Familiarity with modern ELT tools such as Airbyte, Fivetran, Meltano, or dltHub.

• Ability to troubleshoot pipeline failures, performance issues, and data inconsistencies.

• Ability to work closely with clients to solve data issues.

• Ability to work independently and deliver in a contract environment.

WHAT SUCCESS LOOKS LIKE

• Reliable, analytics-ready data pipelines support AI-driven forecasting and attribution intelligence products.

• ELT pipelines are scalable and fault-tolerant.

• dbt models, tests, and documentation follow analytics engineering best practices.

• Workflows are orchestrated and monitored using Dagster.

• Data quality checks and testing strategies are maintained.

• Pipeline failures, performance issues, and data inconsistencies are troubleshot.

• Established team standards for SLAs, code quality, and deployments are followed.

OPPORTUNITY

This hands-on contrac