Senior Data Engineer

Project Description: We are seeking a hands-on Data Engineer to support the Total Fund Management Portfolio Management Technology team. This role focuses on implementing reliable data solutions in a cloud-native environment using established platform tooling and patterns. You are expected to independently design and deliver data solutions with minimal oversight.This is not a role for someone who requires detailed task breakdowns or constant direction. Once objectives and constraints are clear, you are expected to independently drive work to completion, proactively manage risks, communicate progress and trade-offs effectively, and manage stakeholder expectations. Responsibilities: Own timelines and deliverables, proactively managing scope, dependencies, and execution risksIndependently frame, design, and deliver software solutions by engaging stakeholders, clarifying ambiguous requirements, and challenging assumptionsBuild backend services and RESTful APIs aligned to those designsDevelop cloud-native applications (AWS preferred)Implement workflow automation and data pipelines where neededContribute across the full software development lifecycle, including CI/CDEnsure solutions are production-ready, including testing, documentation, and handoverAct as a reliable execution partner, proactively communicating progress, trade-offs, risks, and changes in expectations Mandatory Skills Description: Strong Python with PySparkHands-on experience with Databricks, including developing and operating data workloadsSchema design and data modelling experienceWorking knowledge of Spark sufficient to build and troubleshoot PySpark workloads; deep Spark specialization is not requiredPrior consulting, advisory, or client-facing delivery experienceProven ownership and independent delivery without close supervisionStrong problem-solving skills, including the ability to frame and solve problems in ambiguous situationsStrong communication and stakeholder management skills, including proactive expectation managementDemonstrated adoption of AI-assisted engineering tools and practices as part of day-to-day engineering delivery Nice-to-Have Skills Description: Experience with Apache Iceberg · AWS data services (Glue, Lake Formation) · Workflow orchestration tools (Airflow) · Experience with distributed data processing architectures · Capital markets experience Languages: English: C1 Advanced