Big Data Engineer

Big Data Engineer

Contract · Remote

Annual Compensation Equivalent: $62,400–$166,400/year
Hourly Rate: $30–$80/hour

About the Role

This contract role is for a Big Data Engineer experienced in designing and maintaining large-scale data infrastructure, pipelines, and processing systems.

You’ll apply your engineering expertise to build reliable data solutions and contribute high-quality technical input to the training and improvement of next-generation AI systems. The work involves large-scale data processing, Python development, distributed systems, databases, data quality, and governance.

What You’ll Do

• Design, build, and maintain scalable data pipelines and architectures for large-scale data environments.

• Translate business and technical requirements into reliable data engineering solutions.

• Develop data integration, transformation, and processing workflows using Python and appropriate big data technologies.

• Build, manage, and optimize distributed databases and storage systems for performance, reliability, and scalability.

• Monitor data infrastructure, troubleshoot failures, and improve system availability and performance.

• Implement data quality, security, and governance practices across data pipelines and platforms.

• Apply sound data modeling, ETL, and data warehousing principles to support reliable data systems.

• Collaborate with technical and non-technical stakeholders to understand requirements and communicate implementation decisions.

• Document architectures, processes, technical solutions, and operational procedures clearly.

Requirements

• Proven hands-on experience in big data engineering, including building and maintaining large-scale data pipelines.

• Advanced proficiency in Python for data processing, automation, and system integration.

• Strong understanding of relational and NoSQL databases, including database design, optimization, and administration.

• Experience with distributed data processing frameworks such as Hadoop, Spark, or Flink.

• Solid understanding of data modeling, ETL processes, and data warehousing principles.

• Strong troubleshooting and analytical skills for diagnosing performance, reliability, and data-quality issues.

• Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.

• Detail-oriented, proactive, and comfortable working independently in a remote environment.

Preferred Qualifications

• Experience working in fast-paced or startup-like environments.

• Experience collaborating with globally distributed teams.

• Hands-on experience with cloud-based data platforms and services, including AWS, Google Cloud, or Microsoft Azure.

• Familiarity with MLOps, machine learning infrastructure, or data science workflows.

• Experience building data systems that support analytics, machine learning, or other high-volume data applications.

Who Should Apply

This role is suited to data engineers who have practical experience working with large-scale datasets and distributed data systems. You should be comfortable moving between pipeline development, database optimization, data processing, infrastructure reliability, and data governance.

Strong independent problem-solving and communication skills are important, particularly for engineers working remotely and across multidisciplinary teams.

Compensation

• Annual compensation equivalent: $62,400–$166,400

• Hourly rate: $30–$80/hour

• Annual equivalent is calculated at 40 hours per week × 52 weeks per year.

• Actual earnings will depend on hours worked and the duration of the contract.

Work Arrangement

• Contract position

• Fully remote

• Work focused on large-scale data engineering, distributed processing, databases, pipelines, and data infrastructure

• Collaboration with cross-functional technical and business stakeholders