Senior Data Solutions Engineer

What you will do:

• Evolve the investment data warehouse, pipelines and enterprise data model supporting HOOPP's investment book, market data, and downstream business processes.
• Own the Detect -> Respond -> Prevent cycle across the platform stack, resolving incidents, completing root-cause analysis, and driving preventive actions to closure.
• Investigate investment data issues across positions, transactions, securities, pricing, valuation, and market data, tracing end-to-end flows from source platforms to downstream consumers.
• Create and validate changes to data models, business logic, and data feeds, while protecting data integrity, lineage, auditability, and ICFR controls.
• Design and extend AI-assisted projects using Python, Jupyter notebooks, PowerShell, and alternative AI tools, with clear human validation and approval points.
• Lead projects and provide long-term solutioning by solving the root cause of a problem and partnering with investment, risk, finance, operations, data management, and technology teams to deliver reliable data solutions, operational readiness, and sustainable production support.
• Investigate platform, data pipeline and scheduling challenges using logs, scripts, execution reports, and system diagnostics.
• Execute and enhance governance activities, including production release reconciliations, Quarterly Access Reviews, entitlement management, and privileged-access oversight.
• Maintain and improve runbooks, monitoring, knowledge assets, enterprise job schedules, and operational workflows.
• What you will bring:
• 5+ years of professional software development experience using languages such as Java, Python, C#, or C++.
• Technical fluency across data platforms and operational systems, including Snowflake, Python, SAP HANA, PowerShell, AWS GLUE, and REST APIs, with knowledge of data pipelines, databases, job scheduling, columnar technologies, and production support.
• Strong SQL, data analysis, critical thinking, and creative problem-solving skills to investigate issues, test assumptions and hypotheses, identify root causes, validate results, and develop sustainable solutions. Knowledge of investment products, investment strategies, portfolio theory, valuation models, risk models, and finance theory is an asset.
• Proven experience creating AI agents, skills, or intelligent automation solutions, combined with the ability to think strategically, challenge existing approaches, solve complex problems, and translate emerging AI capabilities into practical business outcomes. Sound judgment to determine next steps, engage the right stakeholders, and balance urgency and quality with governance, compliance, and long-term reliability.
• Accountability for outcomes and a continuous-improvement mindset, with the discipline to carry work through implementation, validation, documentation, and closure. This includes simplifying and automating processes, measuring results, and preventing recurrence.
• Comfortable working across teams, with strong communication skills and the ability to translate complex technical concepts into clear, non-technical language.

This role is eligible to participate in discretionary incentive plan(s), subject to the terms and conditions of the applicable incentive plan text.