We are looking for SeniorData Architect for our Fortune 500 client and their banking client. We’re looking for an engineer with deep experience designing and delivering enterprise-scale big data, streaming, and real-time data integration solutions. The role is focused on solution architecture across Cloudera-based big data platforms, Kafka-based streaming applications, and real-time data integration / analytics solutions, including cloud-hosted data platforms such as Cloudera on AWS or equivalent AWS-native services. The role also provides architectural leadership across Data Solutions, helping shape architecture strategy, design standards, engineering best practices, and the future evolution of the Bank’s data platform capabilities.
This is a long-term remote-first contract position with a location in EU.
Responsibilities
Own the end-to-end solution architecture for large-scale distributed data, streaming, and data integration solutions.
Act as the lead architect for Data Solutions distributed data, integration and platforms, providing architectural direction, governance, design assurance and technical leadership across initiatives, while influencing the evolution of the target architecture and ensuring alignment with enterprise technology strategy, engineering standards and long-term platform objectives.
Accountable for solution architecture across the Enterprise Data Lake, Operational Datastore and associated data platform services within the Cloudera CDP environment on AWS.
Design and document scalable distributed data and streaming solutions across Cloudera, Kafka, API, and cloud platforms, including ingestion, processing, storage, and consumption patterns.
Provide architectural oversight across solution delivery, ensuring consistency, quality and alignment with approved designs.
Work with engineering teams to ensure solutions are deliverable, scalable, secure, supportable, and aligned to enterprise architecture principles.
Review technical designs produced by engineering teams and ensure alignment with the approved solution architecture.
Identify technical risks, dependencies, assumptions, non-functional requirements, and design trade-offs.
-
Support delivery planning by helping break solutions into iterative delivery increments and sprint-level outcomes. Represent solution designs at architecture review boards and governance forums, engaging effectively with business stakeholders, delivery teams, and
enterprise architects.
Develop and promote architectural patterns, engineering standards and best practices across the data platform ecosystem.
Work Conditions
Start Date: October
Location: Remote in EU
Long-term contract based-role: PO till December 2026 with extension to 2027
Requirements
10+ years’ overall IT experience, with significant experience in data platform, integration, or distributed systems delivery.
Proven experience architecting streaming or real-time data applications using Kafka or equivalent event-streaming technologies.
Experience with Kafka consumer architecture, including consumer groups, offsets, retries, dead-letter handling, ordering, partitioning, and scalability.
Proven experience designing solutions on Cloudera CDH/CDP, or substantial experience with equivalent enterprise-scale distributed data platforms.
Experience designing and delivering large-scale data ingestion, transformation, storage, and consumption patterns.
Strong understanding of batch and real-time data processing architectures.
Experience working in complex enterprise environments with multiple systems, vendors, platforms, and governance processes.
Strong understanding of non-functional requirements including performance, scalability, resilience, security, observability, and operational support.
Experience providing architectural leadership across multiple workstreams, programs, or delivery teams.
-
Experience mentoring architects, senior engineers or technical leads and
influencing technical decision-making.
Technical Requirements
Mandatory
Distributed data platforms and data lake architecture on Cloudera CDH/CDP or equivalent platforms.
Event streaming and real-time integration technologies, including Kafka and related messaging patterns.
Large-scale data processing and transformation frameworks such as Spark, Flink, Hive, Impala or equivalent technologies.
Java, Spring Boot, and REST services.
NoSQL and distributed data storage technologies including HBase, Cassandra, or equivalent platforms.
Cloud services, preferably AWS.
DevOps, CI/CD, observability, resilience
Highlights
If you are passionate about Data Engineering, cloud-native architectures, and fintech, this role with our client offers an exciting opportunity to work on impactful projects!
Originally posted on