Maintaining existing design and ensuring the reliability of entire company pipelines on track with SLA. It is possible to redesign the architecture based on the results of the evaluation
Optimize data storage solutions, including BigQuery, Dataflow, and other cloud-native services, to ensure efficient and secure handling of large datasets
Business Collaboration and Strategy:
Work closely with business stakeholders to gather requirements, translate business needs into technical solutions, and ensure that data infrastructure supports key business objectives
Partner with product teams, marketing, finance, and other departments to drive data-driven decision-making across the bank
Data Governance and Security:
Ensure the data infrastructure complies with regulatory requirements and internal security standards, with a particular focus on data integrity, privacy, and governance
Establish best practices for data quality, consistency, and accessibility across the organization
Technical Leadership and Mentorship:
Provide guidance to the data engineering team, ensuring adherence to best practices in cloud architecture, data modeling, and pipeline development
Mentor junior engineers and foster a culture of continuous learning and innovation within the team
Performance Optimization and Innovation:
Continuously monitor and improve data processing performance, scalability, and cost-effectiveness
Stay abreast of emerging trends and technologies in data engineering, recommending tools and practices that align with the bank's evolving needs
Documentation and Reporting:
Maintain detailed documentation of data pipelines, workflows, and architecture to ensure transparency and audit-readiness
Produce regular reports on data platform performance and provide insights on how data solutions are driving business outcomes
Requirement
Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field
Having 5-8 years of experience in data engineering, with a proven track record of leading data engineering projects on Google Cloud
At least 2 years of experience in team management is required
Strong technical expertise in Google Cloud services (BigQuery, Dataflow, Pub/Sub, etc.) and data processing frameworks
Experience in data modeling, ETL/ELT processes, and building real-time and batch data pipelines
Demonstrated ability to work with business stakeholders, translating technical language into business insights and ensuring data solutions support business needs
Knowledge of the banking or financial services industry is highly desirable
Proficiency in SQL, Python, or other relevant programming languages
Strong understanding of data governance, privacy standards (e.g., GDPR), and compliance frameworks
Excellent communication skills and ability to collaborate effectively across departments
