Role Description We are hiring a Senior Data Engineer / Architect to own the technical execution of our Golden Record platform and the broader data infrastructure that extends from it. The Golden Record is our central identity resolution system, resolving messy, overlapping client and instrument data from five source systems into canonical entities. This is not a “build dashboards” role. You will design and build: - Identity Resolution Platform: - The Golden Record — our central system for answering “who is this client?” and “what is this instrument?” - Entity registry, resolver API, and human-in-the-loop review queue for match confirmation. - Integration with external reference data sources (OpenFIGI, EDGAR, GLEIF/LEI) for automated enrichment. - Event Bus + Integration Architecture: - AWS EventBridge as the firm's enterprise event bus. - Ownership of event contracts, schema enforcement, and expansion into trade, research, CRM, and readership domains. - Data Warehouse + Analytics: - Analytical layer built on dbt — staging models, dimensional marts, and bridge tables. - BI dashboards for client coverage, trading activity, readership analytics, and CRM gap analysis. - Data quality monitoring to track resolution rates, alias coverage, and entity drift. Qualifications - 8+ years building data platforms, backend services, or data engineering infrastructure. - Deep experience with AWS serverless (Lambda, API Gateway, EventBridge, Aurora, CDK). - Strong PostgreSQL skills — schema design, query optimization, migrations. - Production experience with event-driven architecture (EventBridge, SNS/SQS, Kafka, or similar). - Hands-on data warehouse and ETL/ELT experience — designed schemas, built pipelines, and operated a warehouse in production. - dbt proficiency — staging/mart patterns, incremental models, testing, documentation. - TypeScript or Python fluency (ideally both; TypeScript is primary for infrastructure). - Experience with entity resolution, master data management, or identity matching problems. - Active use of AI-assisted development tools (Cursor, Claude Code, Copilot, or similar). - Comfort working autonomously in a small team with direct access to business stakeholders. Requirements - Familiarity with broker-dealer operations, trade lifecycle, or research distribution. - Experience with CRM systems (Tier1/S&P Global, Salesforce, or similar). - Data quality frameworks and monitoring (Great Expectations, dbt tests, custom). - Prior experience at a small firm where you owned the full stack, not just one layer. What this role is not - This is not a data science or ML role; the entity resolution logic is rule-based and human-in-the-loop. - This is not a front-end role; the primary UI is BI dashboards and a lightweight HITL review queue. - This is not a large-team management role; you'll be the primary technical executor. - This is not a “move fast and break things” environment; data accuracy matters more than speed. How we work - Small team, high trust; decisions happen in conversation, not in tickets. - Architecture-first; executing a clear vision with significant input on implementation details. - AI-native development; using LLMs and agentic tools throughout our engineering workflow. - Human-in-the-loop is core; building systems where humans are in the critical path. - Legacy respect; wrapping old systems with a clean architecture.

• Architect, design, and manage end‑to‑end Snowflake‑based data platforms , ensuring high performance, scalability, and reliability • Lead data modelling initiatives (dimensional, normalized, and hybrid models) to support complex analytical and financial reporting needs • Design and implement ETL/ELT pipelines , including orchestration, data ingestion, and real‑time or near‑real‑time streaming integrations • Collaborate with stakeholders to analyse data requirements, translating business needs into effective data architecture designs. • Ensure best practices in Snowflake implementation , including performance optimisation, security, access control, and storage management. • Develop advanced SQL and Python scripts for data transformation, automation, and validation • Integrate DevOps practices such as CI/CD and infrastructure‑as‑code into the data engineering lifecycle • Provide architectural leadership and mentoring to data engineers, fostering high standards for delivery, documentation, and collaboration • Support proofs of concept (POCs) and contribute to technical evaluations of tools and technologies

Role Description Für unseren Kunden im Schweizer Versicherungsumfeld suchen wir eine erfahrene Persönlichkeit, der/die aktiv an der operativen Umsetzung von Data Governance und Data Management mitwirkt. In dieser Rolle übernimmst du eine zentrale Funktion bei der nachhaltigen Steuerung, Qualitätssicherung und Nutzung von Unternehmensdaten in einem regulierten Umfeld. - Operative Umsetzung und Weiterentwicklung von Data-Governance- und Data-Management-Strukturen - Mitarbeit und Verantwortung in den Bereichen Data Governance, Data Architecture, Master Data Management (MDM), Data Quality Management (DQM) sowie Data Lifecycle Management - Übersetzung strategischer Vorgaben in konkrete, umsetzbare Prozesse und Standards - Zusammenarbeit mit Fachbereichen, IT, Architektur und Compliance in einer komplexen und regulierten Organisation - Einsatz und Weiterentwicklung einer Data-Governance-Toolchain (z. B. Datenkataloge, Metadaten-, Lineage- oder Qualitätswerkzeuge) - Aktive Mitarbeit in agilen Organisations- und Projektstrukturen Qualifications - Ausgeprägte operative Erfahrung in Data Governance, Data Architecture, MDM, DQM und Data Lifecycle Management - Zwingende Erfahrung im Schweizer Versicherungs- bzw. Krankenkassenumfeld - Nachweisliche Fähigkeit zur Operationalisierung von Data-Management- und Governance-Konzepten (Umsetzung, nicht nur Konzeption) - Fundierte Kenntnisse des DAMA-DMBOK und dessen praktischer Anwendung - Erfahrung in regulierten und/oder komplexen Organisationen - Erfahrung in der Arbeit innerhalb agiler Organisationen - Praxis­erfahrung mit einer Governance Toolchain - Fliessend Deutschkenntnisse, Englischkenntnisse von Vorteil Company Description Die Coopers Group AG ist eine agile Schweizer Recruiting Agentur, die Spezialisten und Führungskräfte in den Bereichen IT, Life Sciences, Engineering und Finance vermittelt. Mit flexiblen Ansätzen bringen wir Kandidat:innen und Unternehmen zusammen, die nicht nur fachlich, sondern auch menschlich zusammenpassen.

Role Description Our client is a globally recognized AI research and engineering organization working at the forefront of large language models and advanced AI systems. They partner with leading enterprises and frontier AI labs to build scalable, high-performance AI solutions that deliver real-world impact. We are hiring a Cloud Data Migration & AI Systems Engineer for a 6 months contract opportunity. In this role, you will work closely with researchers and engineering teams to design, execute, and validate data migration workflows across cloud platforms, while integrating and evaluating LLM/Generative AI components within these systems. This is a high-impact role combining cloud engineering, data systems, and AI evaluation in a cutting-edge environment. - Commitments Required: 8 hours per day with an overlap of 8 hours with PST. - Employment type: Contractor assignment (no medical/paid leave) - Duration of contract: 6+ months - Location: Brazil, India - Interview: 15 min AI-led interview Your Daily Responsibilities - Design and execute data migration workflows across cloud platforms (AWS, GCP, Azure) - Define and optimize migration strategies (online vs offline, scalability, performance trade-offs) - Build and maintain data pipelines and ETL/ELT workflows in distributed systems - Integrate and evaluate LLM / Generative AI components within workflows - Perform system testing and validation, including: - Executing test scenarios - Identifying edge cases and failure points - Debugging and analyzing system behavior - Ensure data integrity, consistency, and performance across systems - Document findings, insights, and technical recommendations - Collaborate with cross-functional teams (engineering, data, product, research) Qualifications - 5+ years of experience with cloud platforms (AWS, GCP, or Azure) and data/storage systems - Strong understanding of data migration strategies and trade-offs - Experience with data pipelines, ETL/ELT workflows, or distributed systems - Hands-on exposure to LLMs / Generative AI (prompting, evaluation, or integration) - Experience in system testing, validation, or QA - Strong debugging and problem-solving skills - Excellent written communication skills