Remote Data Engineer – Data Pipelines and Database Development

Location: Remote within the United States
Employment Type: Full-time
Experience: 2–4 years
Salary: $100,000–$140,000 per year
Schedule: Monday–Friday, with agreed collaboration hours in Eastern Time

The Data Engineer will build and maintain systems that collect, transform, and organize business data. Working with software engineers, analysts, and business teams, you will make information reliable and accessible for reporting and analysis.

The role involves connecting data sources, developing automated pipelines, and creating well-documented datasets. You will investigate processing failures, improve data quality, and monitor the performance and cost of data workloads.

The proposed technology stack includes Python, SQL, Apache Airflow, dbt, AWS, and Snowflake.

Responsibilities

• Develop automated pipelines that collect data from databases, APIs, and business applications.

• Write Python and SQL code to clean, transform, and load information into the data warehouse.

• Build and maintain data models for reporting and analytical use.

• Add checks for missing records, duplicate entries, invalid values, and unexpected changes.

• Monitor scheduled workflows and investigate failed or delayed processing.

• Improve query performance and manage cloud resource usage.

• Work with analysts to define datasets, business metrics, and reporting requirements.

• Document data sources, transformation rules, dependencies, and ownership.

• Apply access controls and follow approved procedures for handling sensitive information.

• Use version control, code reviews, and automated tests to maintain reliable workflows.

• Support deployment of pipeline changes and communicate their impact to downstream users.

Requirements

• Two to four years of experience in data engineering or a closely related technical role.

• Strong SQL skills, including joins, aggregations, window functions, and query optimization.

• Practical Python experience for data processing and automation.

• Experience building ETL or ELT pipelines.

• Understanding of relational databases, data warehouses, and dimensional modeling.

• Familiarity with a workflow orchestration tool such as Apache Airflow.

• Experience using Git and working through code reviews.

• Ability to investigate data discrepancies and explain findings clearly.

• Strong documentation, organization, and independent problem-solving skills.

• Bachelor’s degree in computer science, information systems, or a related subject, or equivalent practical experience.

• Residence in an employer-approved US state and authorization to work in the United States.

Preferred qualifications

• Experience with Snowflake, Amazon Redshift, or Google BigQuery.

• Familiarity with dbt and automated data testing.

• Experience with AWS services such as S3, Glue, or Lambda.

• Knowledge of continuous integration and deployment practices.

• Exposure to streaming data tools such as Kafka.

Work eligibility: The employer must confirm eligible states and whether visa sponsorship is available.

Benefits & Perks

Assumed package for employer review:

• Annual base salary of $100,000–$140,000, depending on experience and location.

• Medical, dental, and vision insurance.

• A 401(k) retirement plan with an employer contribution.

• Twenty days of paid time off, plus company holidays.

• Company-provided laptop and required software.

• Home-office setup allowance.

• Annual learning budget for approved courses and certifications.

• Flexible start and finish times around agreed collaboration hours.

• Regular feedback and opportunities to progress into senior data engineering roles.

How to Apply

Submit your résumé through our job portal. Include relevant experience with data pipelines, SQL, Python, and cloud platforms. Portfolio examples are welcome where you have permission to share them.