Data Engineer

movableink; United States; Remote; USD 125,000 - 170,000; Full time

Job summary

Movable Ink is seeking a data engineer to build and operate data pipelines and warehouse infrastructure that convert campaign and business data into reliable insights for decision-making. You will own the full ELT lifecycle, from source data to production monitoring, collaborating with platform, product engineering, analytics, and reliability teams.

The role requires hands-on experience with large-scale data systems, proficiency in Python/Java/SQL, and modern ELT tools.

Qualifications

• Three+ years of data engineering experience.
• Experience with columnar/OLAP databases at petabyte scale.
• Proficient in Python, Java, or SQL; familiar with Agile, Git, CI/CD.
• Experience with ELT pipelines, production monitoring, and runbooks.
• Knowledge of data architectures like Kimball and medallion.

Responsibilities

• Design, build, test, deploy, and maintain end-to-end ELT pipelines.
• Operate data warehouse infrastructure to boost performance and reliability.
• Aggregate event data with business information to support decisions.
• Collaborate with data platform, product engineering, and analytics partners.
• Coordinate with site reliability to ensure consistent service.

Skills

Python

Java

SQL

Agile development

Git

CI/CD

Infrastructure-as-code

Tools

dbt

Airbyte

Flink

Airflow

Dagster

Job description

Role overview

Build and operate data pipelines and warehouse infrastructure that turn large volumes of campaign and business data into reliable information for decision-making. The work spans the full lifecycle—from sourcing and transforming data to production monitoring and service reliability—and involves close collaboration with platform, product engineering, analytics, and reliability teams.

Responsibilities

• Design, build, test, deploy, and maintain end-to-end ELT pipelines that combine data from multiple sources while controlling costs and meeting service targets.
• Extend and operate data warehouse infrastructure to improve performance, reduce manual effort, and prevent or limit incidents.
• Aggregate and curate event data with internal business information to support business decisions.
• Work with data platform, product engineering, and analytics partners to deliver dependable data products.
• Coordinate with site reliability colleagues to maintain consistent service for internal business teams.

Requirements

• At least three years of data engineering experience.
• Hands-on experience with columnar or OLAP databases at petabyte scale.
• Experience operating production pipelines, including monitoring, alerting, service-level dashboards, and runbooks.
• Strong background in database tooling and automation, modern ELT tools such as dbt, Airbyte, or Flink, and orchestration tools such as Airflow or Dagster.
• Technical understanding of Kimball and medallion data architectures.
• Proficiency in a programming language such as Python, Java, or SQL, plus experience with Agile development, Git, CI/CD, and infrastructure-as-code tools.

Nice to have

• Experience with APIs, reverse ETL, data contracts, AWS data services, data visualization tools, or data lakes using open file formats such as Iceberg.

Benefits and work setup

• Listed base pay is $125,000-170,000 per year; the offer may vary with relevant skills and experience, and may include a bonus.
• Medical, financial, and other benefits are available.