Lead Data Engineer

How is this team contributing to the vision of ProvidenceProvidence Cybersecurity (CYBR) is committed to appropriately protecting all information relating to its caregivers and affiliates, as well as protecting its confidential business information (including information relating to its caregivers, affiliates, and patients).

What will you be responsible for

Data Pipeline Development: Build and maintain robust ETL/ELT pipelines for ingesting and transforming data from multiple sources.
Data Modeling: Design and implement data lake and warehouse solutions to support analytics and reporting.
Collaboration: Work closely with software engineers, data scientists, and business stakeholders to deliver data solutions aligned with organizational goals.
Performance Optimization: Ensure reliability, scalability, and efficiency of data systems in production environments.
Documentation & Governance: Maintain clear documentation and adhere to data governance and compliance standards.

Advanced Analytics and Modeling: Conduct sophisticated data analysis and use innovative models to solve complex business problems. Utilize state-of-the-art statistical and machine learning techniques to extract valuable insights.

Machine Learning Implementation: Develop and deploy advanced machine learning models to address specific business challenges effectively. Evaluate and fine-tune algorithms for improved accuracy and performance.

Collaboration and Stakeholder Engagement:Collaborate with stakeholders and cross-functional teams, including data engineering and product management, to understand requirements and ensure data solutions align with business objectives.

Required Skills

• Proficiency in SQL, Snowflakeand scripting languages for data processing.
• Experience with cloud platforms (Azure preferred).
• Familiarity with data warehousing, big data frameworks.
• Knowledge of DevOps and Agile methodologies for continuous delivery.

Who are we looking for

• Bachelor's degree in related filed, to include computer science, Certifications in Data Engineering,cyber security or equivalent combination of education and experience.
• Experience in working with big and complex data environments.
  Expertise in data integration patterns and tools.
• Proven ability to lead cross-functional teams, drive consensus, and achieve project goals in a dynamic and fast-paced environment.
• Excellent leadership and communication skills, with the ability to effectively communicate technical concepts and strategies to stakeholders at all levels.
• Strong proficiency in Snowflake, SQL, Python, with advanced knowledge of data modelling techniques, dimensional modelling, and data warehousing concepts