Senior Investment Data Engineer

• Design and implement scalable, secure, and maintainable data architectures that support investment and business intelligence initiatives.
• Develop data models, integration frameworks, and data governance standards to ensure consistency and reliability.

Data Pipeline Development

• Design, build, and maintain robust ETL/ELT processes for ingesting, transforming, and delivering large volumes of structured and unstructured data.
• Optimize data workflows to improve efficiency, scalability, and data quality.

Cloud & Platform Engineering

• Develop and manage cloud-based data infrastructure and supporting services.
• Design and maintain automated deployment processes, CI/CD pipelines, and infrastructure-as-code frameworks.

Database Engineering

• Administer and optimize relational and non-relational databases.
• Ensure data integrity, performance, scalability, and availability across enterprise data platforms.

Investment Data Management

• Support the collection, integration, validation, and distribution of investment, portfolio, performance, market, and operational data.
• Partner with business stakeholders to define and maintain critical data assets and reporting requirements.

API & Data Services Development

• Design and implement APIs and data services that enable secure access to investment and business data.
• Develop reliable integrations between internal and external data sources.

Data Quality & Governance

• Establish controls and monitoring processes that ensure accuracy, completeness, and consistency of data.
• Implement data governance best practices and support audit and compliance requirements.

Performance Optimization

• Monitor platform performance and proactively identify opportunities for improvement.
• Optimize data processing, storage, and query performance across systems.

Security & Compliance

• Apply appropriate security controls to protect sensitive business and investment information.
• Support compliance with internal policies and applicable regulatory requirements.

Collaboration & Stakeholder Engagement

• Work closely with technology, operations, analytics, and business teams to deliver data solutions aligned with organizational objectives.
• Translate business requirements into scalable technical solutions.

Technical Leadership

• Mentor junior engineers and promote engineering best practices.
• Conduct code reviews and contribute to the continuous improvement of development standards and processes.

Continuous Improvement

• Stay current with emerging technologies, industry trends, and best practices in data engineering and cloud platforms.
• Recommend and implement improvements that enhance platform capabilities, reliability, and efficiency.

Additional Responsibilities

• Perform other duties and responsibilities as assigned.

We are seeking a highly skilled Senior Investment Data Engineer to lead the design, development, and optimization of enterprise data platforms supporting investment management, analytics, and business operations. This individual will play a critical role in building scalable data pipelines, modernizing data architecture, and delivering reliable, high-quality data solutions that enable informed investment decision-making.

The ideal candidate combines deep technical expertise in data engineering with strong system design capabilities and experience working with complex financial or investment-related datasets. This position offers the opportunity to drive technical innovation, collaborate with cross-functional stakeholders, and influence the future direction of a growing data organization., * 5+ years of experience in data engineering, software engineering, or a related technical discipline.

• Strong experience building and maintaining enterprise data platforms and large-scale data pipelines.
• Experience with SQL and data modeling principles.
• Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
• Strong understanding of software engineering best practices, including version control, automated testing, and CI/CD.
• Excellent analytical, problem-solving, and communication skills.

Education

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Finance, or a related field; equivalent professional experience will also be considered., * Experience working with investment, financial services, capital markets, or asset management data.
• Expertise in building scalable data architectures and distributed data processing solutions.
• Proficiency in Python and modern data engineering tools and frameworks.
• Strong knowledge of data warehousing, ETL/ELT processes, and cloud-native data technologies.
• Experience with big data platforms and technologies.
• Expertise in database design, optimization, and performance tuning.
• Experience developing APIs and data integration services.
• Familiarity with data governance, lineage, metadata management, and data quality frameworks.
• Ability to manage multiple priorities and deliver solutions in a fast-paced environment.
• Proven success collaborating with technical and business stakeholders.
• Experience mentoring engineers and providing technical leadership is highly desirable.