Sr. Lead Data Engineer – Enterprise Risk Management/Remote

Job Description – Sr. Lead Data Engineer – Enterprise Risk Management

Job Summary

We are looking for an experienced Sr. Lead Data Engineer – Enterprise Risk Management to design, develop, and manage scalable data platforms and pipelines that support enterprise risk management initiatives. The candidate will lead data engineering activities, ensure data quality and governance, and collaborate with business and technology teams to deliver risk analytics and reporting solutions.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Develop and manage enterprise data architectures for risk management systems.
• Integrate data from multiple internal and external sources.
• Support risk analytics, compliance reporting, and regulatory requirements.
• Ensure data accuracy, consistency, security, and governance standards.
• Optimize database performance and large-scale data processing workflows.
• Collaborate with risk, compliance, analytics, and business teams.
• Lead technical design discussions and mentor junior data engineers.
• Implement cloud-based data engineering solutions.
• Support automation, monitoring, and troubleshooting of data systems.
• Maintain technical documentation and data flow diagrams.

Required Skills

• Strong experience in data engineering and large-scale data processing.
• Proficiency in SQL, Python, Spark, Hive, or Scala.
• Experience with ETL tools and data pipeline orchestration.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Familiarity with data warehousing and big data technologies.
• Understanding of enterprise risk management and regulatory reporting concepts.
• Experience with databases such as Snowflake, Oracle, SQL Server, PostgreSQL, or Hadoop ecosystems.
• Strong analytical, problem-solving, and leadership skills.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, IT, or related field.

Preferred Qualifications

• Experience in banking, financial services, insurance, or risk management domains.
• Knowledge of data governance and compliance frameworks.
• Exposure to machine learning or advanced analytics platforms.
• Certifications in cloud or data engineering technologies are a plus.