Data Engineer

SaidGig; New York (NY); Remote; USD 100,000 - 150,000; Full time

Benefits offered by this job

Equity compensation

Remote-friendly work model

Health insurance stipend

Job summary

SaidGig is hiring for a remote Senior Data Engineer to build and scale data infrastructure for AI-driven products and research. You will design pipelines that ingest, process, and transform large datasets, while optimizing distributed workflows with Spark and cloud-native tech.

You will implement robust data storage, ensure data quality, and collaborate with researchers and engineers on data-intensive experiments. A focus on Python and SQL is essential for ETL, validation, and analytics.

Qualifications

• Proficient in Python, SQL, and Spark for data processing and analytics.
• Hands-on experience with AWS data services and cloud-native data architecture.
• Experience with large-scale distributed data processing and both SQL/NoSQL databases.

Responsibilities

• Design, build, and maintain scalable pipelines that ingest and transform large datasets from multiple sources.
• Develop distributed processing workflows with Spark and cloud-native technologies.
• Build scalable, high-performing SQL and NoSQL data storage solutions.

Skills

Python

SQL

Apache Spark

AWS

Tools

Matplotlib

Seaborn

Plotly

Job description

Build and scale the data infrastructure behind AI-driven products and research, enabling reliable data processing, experimentation, and model development across large, distributed datasets.

Key Responsibilities

• Design, build, and maintain scalable pipelines that ingest, process, and transform large datasets from multiple sources.
• Develop and optimize distributed processing workflows with Spark and cloud-native technologies.
• Build and maintain scalable, high-performing, reliable SQL and NoSQL data storage solutions.
• Design AWS data architectures for high-volume ingestion, processing, and distribution.
• Write efficient Python and SQL for data extraction, transformation, validation, and analysis.
• Maintain data quality, integrity, monitoring, and operational reliability across pipelines and storage layers.
• Partner with AI researchers, data scientists, and engineers on data-intensive applications and experimentation.
• Implement automation, orchestration, and monitoring to support efficient, scalable data operations.

Qualifications

• Strong Python, SQL, and Apache Spark skills.
• Hands-on experience with AWS data services and cloud-native data architecture.
• Experience with SQL and NoSQL databases and large-scale distributed data processing.
• Strong knowledge of data partitioning, performance optimization, and scalable data architectures.

Preferred Qualifications

• Exposure to AI or machine learning workflows or research environments.
• Experience with Matplotlib, Seaborn, Plotly, or similar data visualization tools.
• Familiarity with data workflows for LLM training, evaluation, or prompt experimentation.

Work Terms

Full-time, remote position.

Compensation and Benefits

• Advertised compensation is $140, 000 to $180, 000 annually.
• The national base salary range is $100, 000 to $150, 000 USD annually.
• Eligible for equity compensation and, depending on role and company policies, performance-based bonuses.
• Benefits include up to 100% reimbursement of health insurance premiums, paid time off, a 401(k) plan with company match, and additional remote-workforce benefits.

Eligibility

Qualified applicants receive consideration without regard to protected characteristics under applicable laws.

Application Support

Applicants who need assistance or a reasonable accommodation during the application process may contact the hiring support team.