Remote Data Jobs · SQL

This position supports PN Operations by gathering, cleaning, and analyzing data to produce accurate reports and dashboards to inform decisions. Working under guidance, this role maintains data quality, documents processes, responds to ad-hoc requests, and develops proficiency in data sets, spreadsheets, and BI tools.

FHI is hiring a hands-on Data Engineer who works independently and thrives in a fast-moving environment. You’ll own and support ETL/data pipelines, integrations, and reporting—diagnosing issues, improving data quality, and partnering with BI to deliver reliable, scalable solutions. Maintain and support ETL, data flows, and reporting processes and build and refine data pipelines, assembling large datasets.

This pivotal role is designed for an emerging professional with experience and possesses a robust interest in public markets, business dynamics, and sophisticated financial analysis. You will act as the primary quantitative auditor of our proprietary SaaS platform's business estimates and investigate discrepancies between internal forecasts and publicly reported data, impacting core product and client messaging.

Support the development of data pipelines, ensuring quality and organization in deliveries under the guidance of more experienced members. Collaborate in the maintenance and evolution of existing solutions, contributing to the continuous improvement of processes. Participate actively in agile rituals, sharing progress and doubts clearly. Demonstrate technical curiosity and a willingness to learn new tools and good data engineering practices. Support the documentation of developed solutions, ensuring traceability and alignment with team standards.

Seeking a detail-oriented Data Scientist with strong analytical skills. Supports legal and regulatory requests by analyzing integrity, ads, and platform data. Collaborates with Legal, Integrity, Product, Engineering, and other partners to gather data and interpret findings to support investigations. Executes analyses to answer complex questions related to litigation, compliance, and internal risk. Communicates findings clearly to both technical and non-technical stakeholders.

Create natural, realistic Q&A pairs that mirror how users interact with SQL query results. Ensure each Q&A pair is linguistically clear, contextually accurate, and logically aligned with SQL outputs. Work across diverse domains including Finance, Cloud Operations, Account Management, and Health. Interpret SQL queries and corresponding result tables. Craft questions that reflect real user scenarios and information needs.

Research and analyze risk patterns occurred on Binance platforms, using data driven thinking and quantitative analysis methodologies to identify, measure, contain and mitigate risks (e.g. fraud trading, spam registration, account takeover, card acquiring risk and payment fraud). Deploy, monitor and assess the effectiveness and stability of variables, rules and models, maintain and iterate the rules/strategies regularly to improve key risk matrix.

You have strong experience with PL/pgSQL, writing efficient SQL queries, tuning performance, and building ETL workflows. You’re comfortable working with Oracle and/or PostgreSQL and navigating complex data structures to support data integration, transformation, and analytics. As a Senior Database Developer, you will play a key role in building and maintaining robust database solutions to support client onboarding, reward processing, data quality, and operational performance.

We are looking for an experienced Netezza Database Administrator with 5+ years of hands-on expertise in managing and supporting Netezza Data Warehouse environments. The candidate should be proficient in administration, performance tuning, and troubleshooting, with the ability to work closely with business and technical teams to ensure optimal data warehouse performance.

We’re looking for an AI/ML Evaluation Engineer to drive the accuracy, reliability, and performance of next-generation AI systems. You’ll build evaluation pipelines, metrics, datasets, and automation that ensure model outputs are consistent, safe, and aligned with real-world expectations. This role is fully technical and highly collaborative, working closely with AI engineers, QA, data scientists, and product leaders.