We are working with a Financial Services firm to support their digital transformation. The Lead Data Engineering will shape the data engineering practice and build the company’s new data and analytics architecture. This role requires deep engineering and data architecture expertise, particularly in greenfield or start-up environments. The candidate will work closely with data architects, engineers, and business stakeholders, influencing data modeling and tool selection. Broad technical skills and hands-on experience are essential.
Responsibilities: Leadership
* Design data solutions and lead data engineering teams.
Data Management
* Establish protocols for data quality, security, and privacy.
Data Pipeline Development
* Design and develop data pipelines ensuring integrity and quality.
Data Modeling
* Implement data models for efficient querying and analysis.
Performance Optimization
* Optimize data components to reduce latency and costs.
Automation
* Automate workflows, validation, and monitoring processes.
Collaboration
* Work with analysts, scientists, engineers, and stakeholders to meet data needs.
Documentation
* Maintain documentation for data pipelines and architecture.
Essential Knowledge & Experience: * Strong background in data engineering or related fields.
* Experience with Google Cloud Platform and mentoring teams.
* Multi-cloud environment experience.
* Strong data architecture and programming skills (Python, SQL).
* Proven experience in data platforms, BI environments, and data modeling.
Desirable Knowledge & Experience: * Experience with Microsoft Azure and multi-cloud setups.
* Knowledge of cloud data management frameworks (e.g., CDMC).
* Familiarity with data governance tools (e.g., Alation).
* Banking sector experience.