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-driven technology company building forecasting and attribution intelligence products powered by high-quality, analytics-ready data. Their teams work cross-functionally across data engineering, analytics, data science, and product to deliver reliable insights that support customer onboarding, reporting workflows, and advanced AI use cases in a fast-moving, execution-focused environment.

Location

Fully remote | 9 AM - 5 PM EST

Role Overview

The Data Engineer will help build and maintain reliable, scalable data pipelines that support analytics, forecasting, and AI-driven products. This is a hands-on, execution-focused contract role centered on data quality, pipeline reliability, and collaboration across analytics, data science, and product teams.

The role operates within a modern analytics engineering stack using Python, dbt, and Dagster, with a strong emphasis on supporting customers onboarding and reporting workflows.

Key Responsibilities

Data Pipeline Development & Orchestration

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

• Orchestrate and monitor data workflows using Dagster

• Troubleshoot pipeline failures, performance issues, and data inconsistencies

• Monitor pipeline health using observability tools and metrics

Analytics Engineering & Data Modeling

• Develop, optimize, and document dbt models following analytics engineering best practices

• Model clean, analytics-ready datasets for BI, forecasting, and machine learning feature consumption

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

Data Quality & Reliability

• Implement and maintain data quality checks and testing strategies

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

Cross-Functional Collaboration

• Collaborate closely with data scientists to support forecasting and AI-driven use cases

• Work cross-functionally with analytics and product teams to ensure data meets business and product requirements

Qualifications

Experience

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

• Hands-on experience working with dbt (Core or Cloud)

• Experience using Dagster or similar orchestration tools

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

• Experience collaborating with Product, Analytics, or Data Science teams

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

Skills

• Strong proficiency in Python, including libraries such as pandas, SQLAlchemy, or psycopg2

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

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

• Strong troubleshooting skills for data pipelines, performance, and data quality issues

• Ability to follow established standards for reliability, testing, and deployment

Opportunity

This contract role offers the opportunity to contribute directly to AI-driven products by building high-impact data infrastructure used for forecasting, attribution, and reporting. You’ll work within a modern analytics engineering stack, collaborate closely with technical teams, and gain hands-on exposure to real-world AI and analytics use cases in a fast-paced, product-driven environment.

Application Process:

To be considered for this role these steps need to be followed:

• Fill in the application form

• Record a video showcasing your skill sets