Remote Big Data Engineer – Build Scalable Data Pipelines

About the role

We are seeking a Remote Big Data Engineer to design, build, and maintain robust data pipelines that support both real‑time and batch processing. You will work closely with data scientists, analysts, and engineering teams to ensure data is reliable, secure, and readily available for analytics across the organization.

Key responsibilities

• Design and implement ETL/ELT pipelines using tools such as Apache Airflow to ingest data from diverse sources.
• Develop and optimise data models for data warehouses and data lakes, supporting reporting and analytical workloads.
• Collaborate with cross‑functional teams to guarantee data quality, governance, and compliance.
• Monitor pipeline performance, troubleshoot failures, and continuously improve system reliability.
• Implement security best practices and data governance frameworks.

Required profile

• Proven experience building scalable data pipelines in a cloud environment.
• Strong understanding of data warehousing concepts, dimensional modeling, and data governance.
• Ability to work independently in a fully remote setting and communicate effectively with distributed teams.

Required skills

• Python
• SQL
• Apache Airflow (or similar workflow orchestration tool)
• AWS, GCP, or Azure cloud platforms
• BigQuery, Redshift, S3
• Apache Spark
• Hadoop ecosystem
• Kafka streaming platform

What we offer

• Competitive salary range of $140K‑$180K per year.
• Fully remote work with flexible hours.
• Opportunity to contribute to a global leader in technology and internet services.
• Access to cutting‑edge data infrastructure and tools.