Senior Data Engineer: Big-Data & AI Pipelines

Seamless; Columbus (OH); Hybrid; USD 120,000 - 160,000; Full time

Job summary

Seamless is seeking a Senior Data Engineer to advance a global data product initiative. You will work cross-functionally on a hybrid data platform, improving coverage, accuracy, and scalability of our product data while solving complex data problems that impact millions of professionals in the lead intelligence space.

The role emphasizes transforming data through AWS-based pipelines, ETL orchestration, analytics, and ML approaches, with ownership of architecture and end-to-end delivery in a

Qualifications

• Minimum 4 year bachelor’s degree in computer science, engineering, mathematics, statistics or related field.
• 5+ years of professional data engineering experience, with end-to-end ownership.
• Able to make and defend architecture decisions with minimal oversight.
• Experience with AWS cloud-based data platforms.
• Strong Python and SQL skills; experience with distributed data processing (Spark) is a must.
• Excellent communication and documentation abilities; ability to translate complex concepts for stakeholders.

Responsibilities

• Large-scale data processing and ETL.
• Data integration and normalization across diverse data sources.
• Data quality and validation.
• Querying and processing performance improvements.
• Cloud-based data infrastructure ownership.
• Data analysis and scoring systems development.
• Automated testing and production reliability.
• Machine learning and statistical approaches to data quality.
• Emerging AI, LLM, and agentic technologies.

Skills

Python

SQL

Data engineering

Spark

AWS

Communication

Troubleshooting

Education

Bachelor's degree in CS/Engineering/Math/Statistics

Tools

Apache Spark

AWS

ETL orchestration

Job description

Seamless is seeking a Senior Data Engineer to advance a global data product initiative. You will work cross-functionally on a hybrid data platform, improving coverage, accuracy, and scalability of our product data while solving complex data problems that impact millions of professionals in the lead intelligence space.

The role emphasizes transforming data through AWS-based pipelines, ETL orchestration, analytics, and ML approaches, with ownership of architecture and end-to-end delivery in a