Data Engineer | $4-$5/hr Remote
Overview
We’re seeking a Data Engineer to design scalable data systems that fuel AI driven products and research. You’ll build and optimize distributed pipelines, manage large datasets across cloud environments, and create reliable architectures that support experimentation and model development. Expect a cloud native stack centered on Python, SQL, Spark, and AWS to power data processing at scale.
What You'll Do8
- 1Create and maintain robust data pipelines to ingest and transform massive datasets from diverse sources
- 2Develop and optimize distributed processing workflows using Spark and cloud services
- 3Design and manage storage solutions across SQL and NoSQL platforms for performance and reliability
- 4Architect data systems on AWS to handle high volume ingestion, processing, and sharing of data
- 5Write efficient Python and SQL to extract, clean, and analyze large data landscapes
- 6Monitor data quality, lineage, and reliability across pipelines and storage layers
- 7Partner with AI researchers, data scientists, and engineers to support data heavy experimentation
- 8Automate orchestration and monitoring to keep data operations scalable and dependable
Requirements5
- 1Strong proficiency with Python and SQL and experience with Apache Spark for distributed processing
- 2Hands on work with AWS data services and cloud based architectures
- 3Experience with both SQL and NoSQL databases and managing large datasets in distributed settings
- 4Solid understanding of data partitioning, performance tuning, and scalable data architectures
- 5Ability to design, implement, and optimize end to end data pipelines and storage solutions
Who Should Apply
The ideal candidate is hands on with data infrastructure, excited by building scalable systems that support AI research, and comfortable collaborating with researchers and engineers to power experimentation.
Salary Insight
Base salary range for this full time role is $100,000 to $150,000 USD; equity and performance bonuses may be offered depending on policy.
Location
Required Skills
Application Tip
Highlight a concrete data pipeline you built end to end, including the tech stack, data volume, and measurable reliability improvements to show impact.
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