Senior Data Engineer

Job not on LinkedIn

🕒 August 19

🏈 Ohio – Remote

🏈 Ohio – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 37%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Seamless.AI

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2018

🤝 B2B

☁️ SaaS

🤖 Artificial Intelligence

💰 $75M Series A on 2021-06

B2B • SaaS • Artificial Intelligence

Seamless. AI is a B2B software company that provides a sales intelligence and lead-generation platform. It aggregates and enriches contact and company data and uses automation and AI-driven matching to help sales and marketing teams find prospects, build lists, and feed CRMs for outreach and pipeline generation.

📋 Description

• Work hands-on with the company and contact profile universe • Improve product data coverage, accuracy, and infrastructure scalability • Solve significant data problems impacting millions of business professionals in the lead intelligence space • Perform large-scale data processing and ETL • Integrate and normalize data across diverse sources • Investigate data quality and validation issues • Query and optimize processing performance • Work with cloud-based data infrastructure • Analyze data and scoring systems • Build automated testing and production reliability processes • Apply machine learning and statistical approaches to data quality • Explore emerging AI, LLM, and agentic technologies • Learn the system and underlying data to determine appropriate technical approaches • Own architecture decisions independently with limited day-to-day guidance • Own projects end-to-end from analysis and planning through implementation and testing • Work with dependencies on other teams' data deliverables and adjust scope • Document architecture decisions and tradeoffs • Troubleshoot production systems across multiple services • Develop consistent, reliable datasets from multiple data sources

🎯 Requirements

• Minimum 4-year bachelor's degree required from a reputable school, concentrated in computer science, engineering, mathematics, statistics, or a related field • 5+ years of professional data engineering experience with end-to-end project ownership • Comfortable making and defending architecture decisions with minimal oversight • Able to own projects end-to-end from analysis/planning through implementation and testing • Able to work with dependencies on other teams' data deliverables and adjust scope accordingly • Clear communicator able to document architecture decisions and tradeoffs • Strong Python and SQL skills • Significant hands-on experience with Apache Spark or comparable distributed data processing technology • Experience designing data processing solutions for large datasets where performance, scalability, and cost are important • Experience with AWS cloud-based data platforms • Experience building and maintaining production ETL or data processing pipelines • Experience with automated testing and validation of data processing code • Strong ability to investigate unfamiliar data and identify data quality or processing problems • Experience using data analysis to evaluate business or product outcomes and guide engineering decisions • Ability to reason about data accuracy and reliability • Experience evaluating changes using historical or production data before deployment • Ability to translate ambiguous data problems into measurable requirements and testable solutions • Strong attention to detail when validating changes to production data • Experience with multi-stage data pipelines and dependencies across systems • Experience with workflow orchestration or comparable distributed processing systems • Ability to troubleshoot production systems across multiple services and identify failure origins • Experience working with data from multiple sources and developing consistent, reliable datasets • Ability to understand and document complex data flows and system behavior • Applicants must be authorized to work in the U.S.

🏖️ Benefits

• Equal opportunity employer valuing diversity • Visa sponsorship is not included in the hiring package