Agile Programming Methodologies, Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Automation, Banking Operations, Banking Services, Best Practices, Big Data, Business Intelligence, Business Model, Business Operations, Cloud Computing, Computer Programming, Computer Science, Continuous Deployment/Delivery, Continuous Integration, Customer Experience, Data Analysis, Data Management, Data Modeling, Data Quality, Data Warehousing, Design Patterns Programming Methodologies, Distributed Computing, Ecosystems, Engineering, Enterprise Architecture, Equal Employment Opportunity (EEO), Financial Services, Genetics, High Availability, High Throughput, Information/Data Security (InfoSec), Interoperability, Java, Leadership, Machine Learning, Medical Conditions, Mentoring, Military, Operational Audit, Performance Tuning/Optimization, Process Improvement, Production Systems, Python Programming/Scripting Language, Realtime Operating System, Regulations, Regulatory Compliance, Reliability Engineering, Risk, Scala Programming Language, Scalable System Development, Service Level Agreement (SLA), Standards Development, State Laws and Regulations, Streaming Technology, Team Lead/Manager, Test Automation, Time Management, Time Tracking, Use Cases
Description
Principal Data Engineer - Real-Time Streaming (Flink)
Role Summary
As a Principal Data Engineer (Real-Time Streaming - Flink), you will be chartered with designing, developing, and operating real-time data systems that drive critical business outcomes. You will lead a team of data engineers and partner with stakeholders to build scalable, event-driven streaming architectures that enable low-latency data access across Citizens business operations.
In addition to core data engineering responsibilities, this role emphasizes Flink-based streaming platforms, event-driven data flow, and highly resilient distributed systems, ensuring that data is continuously processed, governed, and made actionable in near real time.
Specialized Responsibilities
- Serve as a key contributor to the development of real-time data solutions, partnering with stakeholders to define streaming use cases, SLAs, and latency expectations.
- Design and implement event-driven streaming architectures using Flink and related ecosystem technologies.
- Engineer and optimize low-latency, high-throughput data pipelines for operational and analytical workloads.
- Develop and maintain stateful stream processing applications, including windowing, joins, aggregations, and complex event processing.
- Continuously assess data flow across systems, identifying latency bottlenecks, failure points, and data integrity risks, with a focus on real-time processing gaps.
- Implement observability, monitoring, and alerting for streaming systems to ensure availability, performance, and SLA adherence.
- Ensure operational resiliency and stability, including checkpointing, fault tolerance, exactly-once semantics, and recovery strategies in Flink pipelines.
- Lead the development of streaming data models and schemas aligned to business outcomes and event contracts.
- Govern and evolve event schemas and contracts to support enterprise-wide interoperability and data consistency.
- Guide engineering teams on best practices for distributed streaming systems, including back-pressure management, scaling, and partitioning strategies.
- Partner with architecture and platform teams to define standards for real-time data platforms, security, and regulatory compliance within a banking environment.
- Mentor engineers and drive adoption of streaming-first design patterns within Agile delivery teams.
Preferred Technical Expertise
- Advanced expertise in Flink
- Strong experience with event streaming platforms
- Deep understanding of distributed systems design, including fault tolerance, scaling, and high availability
- Experience building stateful stream processing pipelines with windowing, joins, and event-time processing
- Proficiency in low-latency pipeline design and performance optimization
- Experience with cloud-native streaming architectures
- Strong programming skills in Java, Scala, and/or Python with streaming frameworks
- Familiarity with schema management
- Experience integrating streaming data with downstream systems (data lakes, data warehouses, APIs, analytics platforms)
- Knowledge of real-time analytics and monitoring tools
- Understanding of data governance, lineage, and compliance in real-time data environments
Business Outcomes and Impact
- Enable real-time decision-making across banking operations
- Reduce data latency from hours to seconds/minutes, improving responsiveness of business processes
- Improve data reliability and trust through resilient, fault-tolerant streaming pipelines
- Support digital and event-driven business models, including real-time customer experiences
- Increase operational efficiency by unifying batch and streaming data architectures
- Strengthen regulatory and risk capabilities through timely and accurate data availability
- Drive enterprise scalability, enabling growth in transaction volumes and data complexity
Preferred Qualifications
- 8+ years of data engineering experience with demonstrated leadership in streaming data platforms
- Hands-on experience implementing Flink in production environments
- Experience in financial services or banking, with understanding of real-time data use cases such as payments, fraud, or trading
- Experience managing or mentoring engineering teams in Agile delivery environments
- Familiarity with machine learning integration in streaming pipelines (real-time scoring/inference)
- Experience with BI and analytics tools to consume streaming outputs
- Bachelor's degree required; Master's preferred in Computer Science, Engineering, or related discipline
- Certifications in Big Data, AWS, Streaming Technologies, or Agile methodologies preferred
Modernization and Architecture Expectations
- Champion shift from batch-centric architectures to event-driven, streaming-first platforms
- Define and implement enterprise streaming architecture patterns
- Establish standards for data contracts, schema evolution, and event governance
- Build scalable, cloud-native streaming platforms aligned to enterprise architecture strategy
- Integrate streaming with AI/ML platforms to enable real-time inference and intelligent automation
- Drive platform reliability and engineering maturity, including automated testing, CI/CD, and infrastructure-as-code for streaming pipelines
- Promote reusability and modular design in streaming components to accelerate delivery across teams
- Ensure all solutions meet security, compliance, and risk requirements specific to financial institutions
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.