{"id":184017,"url":"https://alion.io/job/avaloq-senior-data-platform-engineer","title":"Senior Data Platform Engineer","company":{"id":5321,"name":"Avaloq","domain":"avaloq.com","url":"https://alion.io/company/avaloq","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":75,"open_postings":8,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":43,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bioggio, Switzerland"],"countries":["CH"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":82000,"max_usd":210000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2324},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Git","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"SIEM","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"Apache Hudi","optional":true},{"name":"Apache Iceberg","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Datadog","optional":true},{"name":"Delta Lake","optional":true},{"name":"ElasticSearch","optional":true},{"name":"Kibana","optional":true},{"name":"Logstash","optional":true},{"name":"Metabase","optional":true},{"name":"Power BI","optional":true},{"name":"Spark","optional":true},{"name":"Splunk","optional":true},{"name":"Superset","optional":true},{"name":"Tableau","optional":true},{"name":"Trino","optional":true}],"status":"live","first_seen_at":"2026-09-01T06:44:45Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-10-18T18:17:06Z","board_verified":true,"closed_at":null,"days_open":47,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":47},"description":"Founded and headquartered in Switzerland, Avaloq is continuously expanding its global footprint with around 2,500 colleagues in 12 countries, and more than 170 clients in 35 countries. We are an industry-leading provider of wealth management technology and services for financial institutions around the world, including private banks and wealth managers, investment managers, as well as retail and neo banks. Our research led approach and continual innovation is powered by the passion and creativity of our colleagues.\nWe are always looking for talented people to join us on our mission to orchestrate the financial ecosystem and democratize access to wealth management. Avaloq offers the opportunity to work closely with some of the world’s leading financial institutions as we jointly develop and shape careers. Championing a collaborative, supportive and flexible work environment empowers our colleagues to reach their full potential.\n 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.\nThis 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.\nThe 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.\nYour key tasks\nData Platform Architecture\nDesign and evolve scalable data platform architectures for security, audit, operational, and analytics data\nDefine data storage strategies, schemas, data models, partitioning, retention, and lifecycle management approaches\nEvaluate and prototype new technologies and architectures to improve scalability, performance, and cost efficiency\nData Engineering & Pipelines\nDesign, build, and maintain batch and streaming data pipelines\nDevelop robust ingestion frameworks for logs, audit data, application events, security telemetry, and operational datasets\nImplement data transformation, enrichment, normalization, correlation, and aggregation processes\nEnsure pipelines are reliable, scalable, observable, and resilient\nData Modeling & Storage\nDesign relational, analytical, and event-based data models\nOptimize database structures, query performance, indexing, and storage efficiency\nSupport the implementation of data lake, warehouse, and lakehouse concepts where appropriate\nData Quality & Governance\nDefine and implement data quality controls across ingestion and transformation layers\nDevelop validation, reconciliation, deduplication, and completeness checks\nSupport data lineage, metadata management, ownership, retention, auditability, and regulatory requirements\nImplement controls for sensitive and regulated data\nPlatform Integration & Analytics Enablement\nIntegrate data from diverse internal and external platforms, applications, databases, APIs, and messaging systems\nDeliver curated datasets that support reporting, analytics, observability, compliance, and security operations\nSupport integration with SIEM, monitoring, and business intelligence platforms\nCollaborate with analytics and reporting teams to improve data accessibility and usability\nEngineering & Automation\nDevelop data engineering services, tooling, and automation using Python and SQL\nContribute to CI/CD practices for data platform components\nSupport infrastructure automation where required, using Terraform and related tooling\nMaintain engineering standards, documentation, and operational procedures\n 8+ years of experience in Data Engineering, Data Platform Engineering, Database Engineering, or a related field\nStrong SQL expertise, including schema design, data modeling, query optimization, indexing, and performance tuning\nExperience designing and operating production-grade batch and/or streaming data pipelines\nExperience with large-scale data platforms and analytical data architectures\nStrong proficiency in Python and SQL\nExperience integrating data from multiple sources, platforms, APIs, and event streams\nStrong understanding of data quality, schema evolution, lineage, governance, and lifecycle management\nExperience with relational databases and analytical storage technologies\nFamiliarity with CI/CD concepts and Git-based development practices\nStrong analytical, problem-solving, and troubleshooting skills\nExperience working with sensitive, security-relevant, or regulated data\nPreferred Qualifications\nExperience with Kafka or other streaming and messaging technologies\nHands-on administration and search query development with Splunk (SPL) or alternative SIEM/observability stacks (Elasticsearch/Logstash/Kibana, Datadog)\nExperience with modern data platform technologies such as Apache Iceberg, Delta Lake, Apache Hudi, Trino, Spark or Parquet\nExperience with data lakehouse architectures\nExperience implementing data quality frameworks and data governance controls\nFamiliarity with data cataloging, lineage, and metadata management solutions\nExperience integrating data platforms with analytics tools such as Apache Superset, Power BI, Tableau, or Metabase\nExperience in banking, fintech, cybersecurity, or other regulated industries\nWorking knowledge of Terraform and cloud-based data platforms\nIt would be a real bonus if you have\nSecurity telemetry and audit-event processing\nSIEM and observability integrations\nCompliance and regulatory reporting datasets\nAI/ML-ready data platform architectures\nReal-time analytics and event-driven architectures\n 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.\nIn 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.\nWe 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.\nPlease 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.","description_format":"text","description_chars":6897,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Flexible 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