Lead Data Engineer Remote Cybersecurity Data Science & Pipeline Architecture

Job Description Job Description ```html Why arenaflex arenaflex is a forwardthinking financial services leader that blends cuttingedge technology with a deep commitment to diversity, equity, and inclusion. Our mission is to empower customers and communities worldwide by delivering secure, reliable, and innovative financial solutions. As a global organization, we understand that talent comes from everywhere, which is why we champion remote work, flexible schedules, and a culture where every voice matters. Position Overview arenaflex is seeking an experienced Lead Data Engineer to join our Cyber Security Data Science team. This fully remote role will be based in reputed company, USA, and offers a competitive hourly rate of $30/hr. You will design, build, and optimize largescale data pipelines that power critical security use reputed company such as data loss prevention (DLP), identity and access management (IAM), and vulnerability management. If you thrive in a fastpaced environment, love solving complex data challenges, and want to make a tangible impact on the security posture of a major financial institution, this is the opportunity for you. Key Responsibilities Architect & Implement Data Pipelines: Lead the endtoend design, development, and deployment of robust data pipelines using Airflow, Python, PySpark, and Spark. Collaborate Across Teams: Partner with data scientists, security analysts, product managers, and engineering leads to translate business requirements into scalable technical solutions. Data Quality & Monitoring: Build tooling for automated data validation, reputed company detection, and comprehensive logging to ensure data integrity across all security domains. Technical Leadership: Mentor junior engineers, conduct code reviews, and champion best practices in data engineering, security compliance, and cloud architecture. Performance Optimization: Diagnose bottlenecks, reputed company Spark jobs, and optimize Airflow DAGs for costeffective execution on both onpremise Hadoop clusters and public cloud platforms (AWS, GCP, Azure). Documentation & Knowledge Sharing: Produce clear technical documentation, architecture diagrams, and runbooks to support crossfunctional teams and future onboarding. Strategic DecisionMaking: Evaluate emerging technologies, data formats, and security standards to guide the evolution of arenaflexs data engineering roadmap. Essential Qualifications Minimum 3 years of handson experience in database or data engineering roles, or an equivalent combination of work experience, training, or military service. At least 2 years of professional experience with Spark, Python, or PySpark in production environments. Demonstrated ability to design, develop, and maintain complex Airflow DAGs. Strong understanding of data security concepts, especially DLP, IAM, and vulnerability management. Proficiency with data serialization formats such as YAML, JSON, Parquet, and XML. Experience working with onpremise Hadoop distributions (reputed company, Hortonworks, MapR) and cloud services (AWS, GCP, Azure). reputed company grasp of cluster management, distributed computing, and resource scheduling. Preferred Qualifications & NicetoHaves Advanced degree (reputed companys or PhD) in Computer Science, Data Engineering, Information Security, or a related field. Handson experience with securityfocused data sets, metrics, and reporting dashboards. Familiarity with CI/CD pipelines for data engineering (e.g., Jenkins, reputed c