Data Engineer ETL SQL @ Fullthrottle.ai®
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Job Details
Overview
Join Fullthrottle.ai, a cutting-edge Marketing Technology SaaS company. Our global software team operates across 5 time zones and 6 countries in a location-independent environment. We are seeking a dynamic and self-directed, mid-level Data Engineer ETL SQL with 3+ years of ETL development experience.
Responsibilities
ETL Responsibilities (80%): Manage ETL process; translate complex business requirements into scalable data solutions; investigate and troubleshoot data and system errors; implement ETL processes to extract, transform, and load data from multiple sources into a data warehouse.
AI Data Preparation / Insights (20%): Clean, transform, and prepare large datasets; handle data quality issues; apply data scaling, normalization, encoding, and feature engineering; design, train, evaluate, and deploy ML models; integrate AI solutions into applications.
Requirements
- Strong proficiency in Python and familiarity with Pandas, NumPy, Scikit-learn, TensorFlow, Keras, PyTorch, etc.
- Excellent SQL skills for complex query optimization.
- Experience with R is a plus.
- Hands-on experience with AWS services such as S3, Lambda, Cloud Formation.
- Agile team collaboration with a focus on sprint reviews and daily deadlines.
- Understanding of ML algorithms and deployment practices.
- Minimum 3 years of ETL development experience required.
- Remote work experience preferred.
Personal Profile
We are looking for long-term team members who are self-directed, results-driven, strong communicators, and experienced in Agile/Scrum environments. Candidates must have a reliable high-speed internet connection and be located within +/- 6 hours of US Eastern Standard Time.
Key skills/competency
- ETL
- SQL
- Python
- AWS
- Data Warehousing
- ML
- Data Transformation
- Agile
- AI
- Remote Collaboration
How to Get Hired at Fullthrottle.ai®
🎯 Tips for Getting Hired
- Research Fullthrottle.ai: Understand the company's culture and mission.
- Tailor your resume: Highlight ETL, SQL, Python, and AWS skills.
- Showcase remote experience: Emphasize distributed team work.
- Prepare for technical interviews: Review ETL and ML scenarios.
- Practice Agile scenarios: Prepare examples from sprint work.