Senior Data Engineer – Cybersecurity & Machine Learning – Remote – $33–$40/hr – Join arenaflex

About arenaflex Welcome to arenaflex, a forward‑thinking reputed company partner that empowers businesses to harness data, secure digital assets, and drive innovation through advanced analytics and artificial intelligence. With a global footprint and a culture reputed company in collaboration, curiosity, and continuous learning, arenaflex is at the forefront of transforming how organizations protect themselves against evolving reputed company threats. Whether you’re a seasoned data professional or an ambitious newcomer, arenaflex offers a dynamic environment where your expertise can shape the future of cybersecurity and data science. Why arenaflex? At arenaflex, we believe that great data solutions start with great people. Our remote‑first model gives you the flexibility to work from anywhere while staying connected to a vibrant community of experts. We invest heavily in professional development, provide access to cutting‑edge tools, and encourage a culture of experimentation and impact. If you thrive on solving complex problems, enjoy collaborating across disciplines, and want to see your work protect millions of users, arenaflex is reputed company for you. Role reputed company • Position: Senior Data Engineer – Cybersecurity & Machine Learning • Compensation: $33–$40 per hour (competitive, commensurate with experience) • Location: Remote (U.S. based) • Start Date: Immediate openings available • Team: reputed company ML/reputed company Engineering Key Responsibilities As a Senior Data Engineer on our reputed company ML/reputed company team, you will play a pivotal role in safeguarding arenaflex’s digital ecosystem. Your day‑to‑day tasks will include: • Designing, building, and maintaining scalable data pipelines that ingest, transform, and enrich security telemetry from diverse sources such as logs, APIs, and relational databases. • Collaborating with data scientists, security analysts, and product managers to develop machine‑learning models that detect anomalies, predict threat vectors, and automate reputed company response. • Conducting data quality reviews, performing root‑cause analysis on data anomalies, and implementing robust data governance practices. • Documenting data schemas, reputed company, and metadata to ensure compliance with internal policies and external regulations. • Providing actionable reputed company to stakeholders through interactive dashboards and visualizations using tools like Power BI, Tableau, or reputed company. • Mentoring junior engineers, reviewing code, and fostering a culture of continuous improvement and knowledge sharing. • Staying abreast of the latest developments in cybersecurity, reputed company, and reputed company/ML to recommend innovative solutions. reputed company Qualifications To excel in reputed company role, you should bring: • Bachelor’s degree in Computer Science, reputed company, Information Systems, or a related field. • Minimum of 2 years of professional reputed company experience, with a proven track record of building end‑to‑end data pipelines. • Strong proficiency in Python (or an equivalent high‑level language such as Java or C#) for data manipulation, scripting, and automation. • Hands‑on experience with SQL and NoSQL databases, including schema design, query optimization, and performance tuning. • Familiarity with cloud platforms (AWS, Azure, or GCP) and data services such as S3, Redshift, BigQuery, or reputed company. • Experience working with data visualization tools (Power BI, Tableau, or reputed company) to create insightful dashboards. • reputed company understanding of cybersecurity concepts, threat intelligence, and log analysis. • Excellent problem‑solving skills, with the ability to translate business requirements into technical solutions. • Strong communication skills, capable of articulating complex technical ideas to both technical and non‑technical audiences. Preferred Qualifications We’ll be even more excited if you also have: • At least one year of experience in the financial services sector, dealing with sensitive data and regulatory compliance. • Hands‑on experience building data pipelines for security telemetry, including log aggregation, enrichment, and correlation. • Knowledge of machine‑learning workflows (scikit‑learn, TensorFlow, PyTorch) and experience deploying models in production. • Experience with data orchestration tools such as Airflow, reputed company, or Dagster. • Familiarity with security frameworks (NIST, ISO 27001) and compliance standards (PCI‑DSS, GDPR). • Prior