Remote Big Data Engineer — Build Scalable Pipelines

Recruitment Room; Österreich; Remote; EUR 54,000 - 145,000; Full time

Job summary

Appsierra Group in a fully remote contract role seeks a Big Data Engineer to design and maintain large-scale data infrastructure, pipelines, and processing systems.

You will apply Python development, work with distributed systems and both SQL and NoSQL databases, implement data quality and governance, and collaborate with stakeholders to deliver reliable data solutions for AI training and analytics.

Qualifications

• Hands-on big data engineering experience with large-scale pipelines.
• Advanced Python for data processing and automation.
• Strong relational and NoSQL database knowledge and tuning.
• Experience with Hadoop, Spark, or Flink.
• Knowledge of data modeling, ETL, and data warehousing.
• Strong problem-solving and communication, especially remotely.

Responsibilities

• Design, build, and maintain scalable data pipelines and architectures for large-scale data environments.
• Translate requirements into reliable data engineering solutions.
• Develop data integration, transformation, and processing workflows using Python and big data tech.
• Manage distributed databases and storage systems for performance and reliability.
• Monitor data infrastructure, troubleshoot failures, and improve availability.
• Implement data quality, security, and governance across pipelines.
• Apply data modeling, ETL, and warehousing principles.
• Collaborate with stakeholders to communicate implementation decisions.
• Document architectures, processes, and procedures clearly.

Skills

Python

Big data pipelines

Distributed systems

Database design

Data modeling

Troubleshooting

Communication

Remote work

Tools

Hadoop

Spark

Flink

SQL

NoSQL

Cloud platforms

Job description

Appsierra Group in a fully remote contract role seeks a Big Data Engineer to design and maintain large-scale data infrastructure, pipelines, and processing systems.

You will apply Python development, work with distributed systems and both SQL and NoSQL databases, implement data quality and governance, and collaborate with stakeholders to deliver reliable data solutions for AI training and analytics.