Senior Data Architect

About the role

We are seeking a Senior Data Architect to serve as a technical lead shaping the future of our data platform in the financial services space. This is a high-impact, hands-on leadership role — you will own architectural direction, drive integration strategy, and act as a trusted technical advisor to both internal stakeholders and external clients.

Responsibilities

• Data Platform Leadership
  • Define and evolve the enterprise data architecture strategy, ensuring scalability, reliability, and governance across the platform.
  • Lead the design and implementation of cloud data warehousing and lakehouse solutions, with a focus on Snowflake and Databricks, aligned with financial services data requirements.
  • Establish data modeling standards, data quality frameworks, and best practices across engineering teams.
  • Champion data governance, security, and compliance practices in alignment with financial industry regulations (e.g., SOC 2, GDPR, CCPA).
• Integrations & API Development
  • Partner with Product Management and business stakeholders to design and deliver robust data integrations and APIs (REST, GraphQL, ETL/ELT pipelines).
  • Architect scalable, reusable integration patterns that connect internal systems, third-party platforms, and client data ecosystems.
  • Define API contracts, data schemas, and integration standards that support both internal development teams and external partners.
  • Translate complex business and regulatory requirements into sound, implementable technical designs.
• Implementation Support
  • Serve as a technical expert and Engineering partner to pre-sales and implementation teams providing architectural guidance where needed to ensure successful client onboarding.
  • Engage with critical prospects and clients as needed, helping build trusted relationships with their senior technical stakeholders.

Requirements

• 8+ years of experience in data architecture or data engineering.
• Proven expertise in cloud data platforms such as Snowflake, Databricks, including data modeling, performance tuning, and cost optimization.
• Hands-on experience designing and building REST APIs and ETL/ELT pipelines at scale.
• Strong proficiency with real-time and streaming data platforms such as Kafka, Flink, and Spark.
• Hands-on experience with modern data orchestration and transformation tools such as dbt and Apache Airflow.
• Experience with data testing frameworks, pipeline observability, and monitoring practices that ensure data quality, reliability, and operational visibility in production environments.
• Experience with major cloud platforms (AWS, Azure, or GCP), including cloud-native data services, networking, and security.
• Experience with vector database or embedding infrastructure in production.
• Experience integrating unstructured data (documents, PDFs, presentations) into a structured data platform, including extraction, normalisation, and lineage back to source artefacts.
• Demonstrated ability to drive technical strategy and lead cross-functional projects.
• Working understanding of LLM and RAG architectures, including tenant-aware retrieval, context isolation, and the data quality and lineage prerequisites for safe deployment.
• Strong communication skills with the ability to translate complex technical concepts for executive and non-technical audiences.

Qualifications

We cultivate a culture of innovation and collaboration, where your ideas matter. We empower our team members to take initiative, learn continuously, and thrive in a supportive environment.