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