AMINA Bank
Website:
aminagroup.com
Job details:
About AMINA
Founded in April 2018 and headquartered in Zug, AMINA Bank is a pioneer in the financial industry. In August 2019, AMINA received a Swiss banking and securities dealer license from FINMA. The broad, vertically integrated spectrum of services, combined with the highest security standards, make AMINA’s value proposition unique.
AMINA operates globally from its regulated hubs in Switzerland, Abu Dhabi, and Hong Kong to offer fiat and crypto services to progressive investors, traditional and crypto-native alike, whether individuals, corporates, or institutions.
CVVC Global Report and CB Insights named AMINA as one of the Top 50 Companies within the blockchain ecosystem. Aite Group awarded AMINA their 2021 Digital Wealth Management Impact Innovation Award in the ‘Digital Startup of the Year’ category, and LinkedIn listed AMINA as one of the Top Startups 2021 in Switzerland. In 2022, AMINA won the Digital Assets Offering or Service at the WealthBriefing Swiss EAM Awards, and the bank was also recognised for its product offering SEBAX and won the Best ETP of the Year award at the Swiss ETF Awards 2022. In 2023, AMINA won the European WealthBriefing Award in the Digital Assets Solution, Fund Manager category.
AMINA India is a wholly owned subsidiary of AMINA Bank AG. AMINA India acts as a virtual extension of the bank supporting activities spanning trading & liquidity management, digital assets research, marketing, investment solutions, risk management, account management, mid/back-office, product management, technology & engineering, IT support, finance and human resources.
About the Role
We are looking for a hands-on Data Architect with strong expertise in Microsoft Azure, particularly Azure Synapse Analytics & Fabric, to design and evolve scalable enterprise data platforms. The role combines architecture, technical leadership and hands-on engineering.
You will define data models, integration patterns and engineering standards, guide implementation, and ensure solutions meet business requirements for security, governance, reliability, performance and cost.
Responsibilities
- Define and implement end-to-end data architecture across Data Lake, Data Warehouse, Lakehouse and Analytics platforms.
- Define conceptual, logical, physical and dimensional models, source-independent enterprise models, data contracts and schema-evolution approaches.
- Maintain architecture decisions and roadmaps; assess data technologies, including adoption, coexistence and migration options.
- Design scalable batch, incremental and real-time/streaming data processing solutions.
- Provide deep technical expertise across Azure Synapse, Azure Data Factory, ADLS Gen2, Event Hubs and Databricks.
- Design Medallion/Lakehouse architectures, data models, ingestion frameworks and reusable engineering patterns.
- Drive performance, scalability, reliability and Azure cost optimization.
- Develop technical POCs and prototypes; review SQL, PySpark and data pipelines.
- Troubleshoot complex data platform and pipeline issues and provide technical direction to Data Engineering teams.
- Establish architecture, security, governance, CI/CD and data engineering standards.
- Evaluate and contribute to adoption of Microsoft Fabric as part of the future data platform strategy.
- Partner with Engineering, BI, Cloud, Security and business teams to translate requirements into practical technical solutions.
- Ability to balance architecture quality, delivery timelines, performance and cost. Ability to challenge existing designs and propose pragmatic alternatives.
- Strong understanding of technology trade-offs rather than being tied to a single technology.
Experience
- Strong hands-on experience with Microsoft Azure data platforms.
- Deep expertise in Azure Synapse Analytics.
- Strong experience with Azure Data Factory and ADLS Gen2.
- Strong understanding of Data Lake and Data Warehouse architectures.
- Experience designing batch and incremental data processing frameworks.
- Strong understanding of real-time/streaming architectures.
- Strong SQL and data modelling skills.
- Hands-on experience with Spark/PySpark and distributed data processing.
- Experience with large-scale enterprise data platforms and complex data integration.
- Strong understanding of cloud architecture, scalability, performance and cost optimization.
- Experience with CI/CD, DevOps and infrastructure/environment management for data platforms.
- Ability to address performance, scalability, observability, recovery and cost requirements, document architecture decisions and guide engineering teams
Good to Have
- Experience with Microsoft Fabric.
- Azure Databricks experience.
- Kafka / Confluent experience.
- Microsoft Purview.
- Event-driven architecture.
- Experience with Delta Lake / Lakehouse architecture.
- Experience with Power BI and enterprise semantic models.
- Experience with financial services, banking or other regulated industries.
Ideal Candidate
The ideal candidate can architect a solution, prototype it, troubleshoot it and guide engineering teams to deliver it. They balance architecture quality with delivery timelines, reliability, performance and cost; challenge existing designs constructively; and select technologies based on requirements rather than product preference.
Click on Apply to know more.
