Director of Data Operations – Operational Support & Data Platform Stability

Description

Role Summary

As a Director of Data Operations focused on Operational Support and Data Platform Stability, you will provide senior technical leadership to a team of data engineers responsible for operating, and continuously improving enterprise-scale data platforms. This role extends beyond traditional engineering to ensure high availability, resiliency, and performance of critical data pipelines and systems supporting core banking and analytics functions.

You will partner with business and technology stakeholders to modernize data ecosystems using AI-driven automation, Lakehouse architecture, and cloud-native platforms, while ensuring operational excellence. Your leadership will drive consistent, scalable, and reliable data delivery across the enterprise, enabling downstream analytics, regulatory reporting, and customer-facing applications.

Specialized Responsibilities

• Provide hands-on leadership for 24x7 operational support and reliability engineering of enterprise data platforms
• Ensure data pipeline stability, resiliency, and performance at scale, including proactive monitoring and incident prevention
• Establish and enforce AI-driven operational automation, including self-healing pipelines, anomaly detection, and predictive failure analysis
• Partner with stakeholders to define SLAs, SLOs, and operational KPIs for data systems across critical business domains
• Oversee root cause analysis and resolution of data incidents, pipeline failures, and performance bottlenecks
• Drive modernization of legacy ETL/ELT processes into cloud-native, event-driven, and scalable data frameworks
• Lead implementation of observability frameworks, including logging, tracing, metrics, and lineage tracking
• Standardize data engineering lifecycle practices, including CI/CD, automated testing, and release governance
• Optimize data platforms for cost, performance, and throughput efficiency across distributed systems
• Collaborate across teams to ensure downstream data consumption readiness, including analytics, reporting, AI/ML, and regulatory use cases
• Mentor and develop engineering teams in site reliability engineering (SRE) principles and operational excellence

Preferred Technical Expertise

• Advanced experience with Lakehouse architectures (e.g., Delta Lake, Apache Iceberg, Hudi) and related engineering patterns
• Deep expertise in cloud-based data ecosystems (AWS, Azure, or GCP), including distributed storage and compute
• Strong experience with streaming and event-driven processing (e.g., Kafka, Spark Streaming, Flink)
• Expertise in data pipeline orchestration and automation tools (Airflow, Dagster, native cloud orchestration)
• Proficiency in AI/ML-driven operational analytics, including anomaly detection, forecasting, and optimization models
• Experience implementing data observability and monitoring platforms (e.g., Monte Carlo, Datadog, Prometheus, CloudWatch)
• Advanced programming experience in Python, Java/Scala, SQL, and distributed processing frameworks
• Expertise in performance tuning for large-scale data systems, including storage optimization, partitioning, and indexing strategies
• Familiarity with DevOps and SRE practices, including Infrastructure as Code (Terraform, CloudFormation)

Business Outcomes and Impact

• Improved data platform stability and uptime, ensuring reliable delivery of mission-critical data assets
• Reduced mean time to detect (MTTD) and mean time to resolve (MTTR) for data incidents
• Increased operational efficiency through automation, reducing manual intervention and support overhead
• Enhanced data pipeline scalability and performance, enabling high-volume, low-latency data processing
• Accelerated enterprise data modernization, transitioning from legacy systems to cloud-native architectures
• Improved data quality and trust, supporting regulatory compliance and critical business decision-making
• Optimized infrastructure cost and utilization across distributed cloud environments
• Enabled faster downstream analytics and AI/ML innovation through reliable, well-governed data pipelines

Preferred Qualifications

• 12+ years of experience in data engineering, with significant focus on large-scale operational support and platform reliability
• Proven experience leading teams in enterprise data platform operations within financial services or regulated industries
• Demonstrated expertise in cloud migration and data modernization initiatives
• Experience implementing AI-driven automation in production data environments
• Strong understanding of consumer and commercial banking data domains and regulatory requirements
• Experience with Agile delivery models and cross-functional stakeholder engagement
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• Relevant certifications in Cloud, Big Data, or Agile methodologies

Modernization and Architecture Expectations

• Lead the transition to Lakehouse-driven architectures to unify analytics, AI, and operational workloads
• Establish cloud-first, modular data platform designs supporting scalability and resilience
• Implement event-driven, loosely coupled data pipelines to improve adaptability and real-time capabilities
• Drive adoption of AI-powered operational intelligence, including automated remediation and predictive monitoring
• Standardize data platform observability, governance, and lineage frameworks
• Replace legacy ETL systems with modern, scalable, and metadata-driven pipeline architectures
• Ensure all data systems are designed with resiliency, fault tolerance, and failover capabilities as core principles
• Embed security, compliance, and data privacy controls into platform architecture by design

Hours & Work Schedule

• Hours per Week: 40
• Work Schedule: Monday-Friday
• Hybrid: 4 days per week on-site

Some job boards have started using jobseeker-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague’s or a dependent’s reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.