About this role
We are seeking a Senior Data Platform Engineer to design, build, and operate a scalable, secure, and governed data platform supporting security, audit, operational, and analytics workloads.
This role is primarily focused on data engineering and data platform development, including data architecture, ingestion pipelines, data modeling, quality controls, governance, and integration with analytics and security platforms. The successful candidate will have strong experience designing and operating data platforms, building reliable batch and streaming pipelines, and managing large volumes of structured and semi-structured data.
The role requires close collaboration with security, infrastructure, and application teams to deliver trusted, high-quality data that enables monitoring, reporting, threat detection, compliance, and business insights.
Your key tasks
Data Platform Architecture
Design and evolve scalable data platform architectures for security, audit, operational, and analytics dataDefine data storage strategies, schemas, data models, partitioning, retention, and lifecycle management approachesEvaluate and prototype new technologies and architectures to improve scalability, performance, and cost efficiencyData Engineering & Pipelines
Design, build, and maintain batch and streaming data pipelinesDevelop robust ingestion frameworks for logs, audit data, application events, security telemetry, and operational datasetsImplement data transformation, enrichment, normalization, correlation, and aggregation processesEnsure pipelines are reliable, scalable, observable, and resilientData Modeling & Storage
Design relational, analytical, and event-based data modelsOptimize database structures, query performance, indexing, and storage efficiencySupport the implementation of data lake, warehouse, and lakehouse concepts where appropriateData Quality & Governance
Define and implement data quality controls across ingestion and transformation layersDevelop validation, reconciliation, deduplication, and completeness checksSupport data lineage, metadata management, ownership, retention, auditability, and regulatory requirementsImplement controls for sensitive and regulated dataPlatform Integration & Analytics Enablement
Integrate data from diverse internal and external platforms, applications, databases, APIs, and messaging systemsDeliver curated datasets that support reporting, analytics, observability, compliance, and security operationsSupport integration with SIEM, monitoring, and business intelligence platformsCollaborate with analytics and reporting teams to improve data accessibility and usabilityEngineering & Automation
Develop data engineering services, tooling, and automation using Python and SQLContribute to CI/CD practices for data platform componentsSupport infrastructure automation where required, using Terraform and related toolingMaintain engineering standards, documentation, and operational procedures 8+ years of experience in Data Engineering, Data Platform Engineering, Database Engineering, or a related fieldStrong SQL expertise, including schema design, data modeling, query optimization, indexing, and performance tuningExperience designing and operating production-grade batch and/or streaming data pipelinesExperience with large-scale data platforms and analytical data architecturesStrong proficiency in Python and SQLExperience integrating data from multiple sources, platforms, APIs, and event streamsStrong understanding of data quality, schema evolution, lineage, governance, and lifecycle managementExperience with relational databases and analytical storage technologiesFamiliarity with CI/CD concepts and Git-based development practicesStrong analytical, problem-solving, and troubleshooting skillsExperience working with sensitive, security-relevant, or regulated dataPreferred Qualifications
Experience with Kafka or other streaming and messaging technologiesHands-on administration and search query development with Splunk (SPL) or alternative SIEM/observability stacks (Elasticsearch/Logstash/Kibana, Datadog)Experience with modern data platform technologies such as Apache Iceberg, Delta Lake, Apache Hudi, Trino, Spark or ParquetExperience with data lakehouse architecturesExperience implementing data quality frameworks and data governance controlsFamiliarity with data cataloging, lineage, and metadata management solutionsExperience integrating data platforms with analytics tools such as Apache Superset, Power BI, Tableau, or MetabaseExperience in banking, fintech, cybersecurity, or other regulated industriesWorking knowledge of Terraform and cloud-based data platformsIt would be a real bonus if you have
Security telemetry and audit-event processingSIEM and observability integrationsCompliance and regulatory reporting datasetsAI/ML-ready data platform architecturesReal-time analytics and event-driven architectures We realize that managing work life balance is a challenge we all face in our daily lives and in order to support with this we are pleased to offer hybrid and flexible working for most of our Avaloqers to maintain work life balance and still continue our fantastic Avaloq culture in our global offices.
In Avaloq we are proud to embrace diversity and understand the success of our business is built on the power of different opinions, we are whole heartedly committed to fostering an equal opportunity environment and inclusive culture where you can be your true authentic self.
We hire, compensate and promote regardless of origin, age, gender identity, sexual orientation or any other fantastic traits that make us all unique, we have done our best to write this advert in an inclusive and neutral way.
Please be aware that we will not accept speculative CV submissions for any of our roles from recruitment agencies, and any unsolicited candidate submissions will be exempt from any payment expectations.
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