Data Analyst

Halcyon Labs is one of the fastest-growing WealthTech platforms for independent asset managers in Switzerland. Built on modern cloud technologies, we provide a fully SaaS-based solution designed to simplify and centralize wealth management operations. Our mission is to become the future data hub for the wealth management and private banking industry. We are looking for a Data Analyst to join our team and work on cloud-based data systems that transform raw financial data into high-quality datasets powering our product. The role includes financial instrument modelling within a Portfolio Management System (PMS), so strong knowledge of equities, bonds, derivatives, and funds is essential. You will collaborate with banks and wealth management institutions, primarily in Switzerland, as we continue to scale internationally. Responsibilities: Design, maintain, and improve data models for financial instruments within a PMS environment. Transform and standardize external custodian and market data into consistent internal formats. Build and maintain data pipelines for financial data ingestion and processing (ETL/ELT). Ensure high data quality through validation, reconciliation, and quality assurance processes. Optimize data transformation workflows with focus on scalability, reliability, and performance. Automate manual processes across data transformation and data quality workflows. Work with external data providers, banks, and wealth management clients to integrate financial data. Collaborate with Product, Engineering, and Customer Success teams to improve data management practices. Contribute to continuous improvement of data structures, documentation, and standards. Tech stack & tools: Our platform is fully built on Microsoft Azure cloud. Core stack: Microsoft Azure (Storage, Data Factory, DevOps, Pipelines & Releases) SQL (data analysis, validation, troubleshooting, performance optimization) Python (automation, scripting, data processing) Git (version control) Additional tools: Visual Studio / Visual Studio Code Postman (API testing) JSON- based transformation configurations Internal ETL and data ingestion tools Engineering practices: CI/CD -driven deployments Cloud- first architecture Agile / DevOps- oriented collaboration Requirements: Minimum 2 years of professional experience in Data Analytics or a similar role. Experience in financial data modelling ; knowledge of instrument modelling in a PMS environment is a strong advantage. Strong proficiency in SQL , including experience with large datasets and query performance optimization. Experience in d esigning, building, and maintaining data pipelines (ETL/ELT). Experience in data transformation workflows and automation of data processing . Experience in data validation and data quality assurance processes. Experience with version control systems (e.g. Git). Proficiency in Python is an additional advantage. Solid understanding of financial instruments (e.g. equities, bonds, derivatives, funds) Strong analytical thinking and excellent attention to detail. Ability to work with large datasets and performance-oriented mindset in SQL/data processing. Strong team player with good communication skills and a collaborative approach. Professional level of English (spoken and written). Nice to have: Understanding of data modelling principles (e.g. normalization, dimensional modelling). Experience working with external data sources (e.g. vendor data, APIs, market data feeds). Experience in financial services or investment/portfolio management environments. We offer: Access to private medical care (Medicover) and a Multisport card to support your health and wellbeing. Flexible working hours with a hybrid/remote setup , including workation options. Annual training budget and access to courses and conferences to support continuous professional development. Fast-paced career growth in a scaling organization with real business impact. Opportunity to work on innovative, tech-driven projects in the financial sector. Flat organizational structure with fast decision-making and minimal bureaucracy. Strong team culture with i ntegration events, offsites, and regular team lunches. Supportive environment of experienced, collaborative professionals focused on problem-solving and innovation.