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Lead Data Platform Engineer - AI Foundation

posted by: spj_bot

Senior Data Engineer - AI-First Fintech Platform

Location: Remote - Fully Remote - Across Europe

Compensation: $120K - $140K

We are a rapidly growing fintech and crypto platform undergoing an AI-first transformation. We are seeking a strategic, high-impact, and high-ownership Senior Data Engineer to build the foundational data infrastructure that powers our cutting-edge AI features.

You will report directly to the CTO and work closely with our Machine Learning (ML) team to consolidate and govern our data ecosystem (including PostgreSQL, Kafka, BigQuery, and GCS) into a clean, governed, and ML-ready platform. Your contributions will directly enable critical AI functionality across our product suite.

This role is responsible for the end-to-end design, implementation, and governance of our core data platform, ensuring high performance and readiness for ML applications.

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Senior Software Engineer (Remote - US or Canada)

posted by: spj_bot

About Jobgether:

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Senior Software Engineer in US / Canada.

We are looking for a Senior Software Engineer to help build scalable, data-intensive applications that power mission-critical systems. In this role, you will work on designing ETL pipelines, building high-performance APIs, and transforming large volumes of raw data into impactful products. You’ll collaborate with cross-functional teams including data science, product, and engineering, and contribute to backend infrastructure and data platform initiatives. This role is ideal for engineers with strong backend and data engineering experience, a passion for performance and scalability, and a hands-on approach to building systems from the ground up.

Accountabilities:

·         Design and implement ETL pipelines capable of processing large-scale datasets efficiently.

·         Build and maintain robust APIs for data retrieval, including support for complex query types.

·         Architect scalable data storage and retrieval systems using SQL/NoSQL technologies.

·         Transform raw data into structured, high-value data products to support business and operational decisions.

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