Data Engineer
4 days ago
Our proprietary platform, enhanced by machine learning and robotic process automation, gives clients real-time insights and unmatched control over their operations. Alongside our technology, we offer award-winning service through our team-based approach -- led by a deeply experienced team of industry experts. Our solutions span the full investment lifecycle, including fund accounting, middle office, risk, compliance, tax, and investor services.
We're a future-focused company, empowering our people through a robust career development framework, clear career trajectories with structured learning paths, training, and progression plans. We invest in leadership development and in our collaborative culture, creating space for talent to grow. Our corporate values - Relationships, Support, Innovation, and Expertise - create a sense of shared purpose and belonging, and we recognize our employees sit at the core of our success. We continue to innovate and evolve through our employees, working together to achieve our shared vision and mission.
HedgeServ supports employees through a variety of offerings, including remote and hybrid working arrangements, and fully paid comprehensive health and well-being benefits. We've been recognized as an employer of choice, earning a top 100 workplaces designation.
Founded in 2008, HedgeServ has grown into a global organization with over 2,000 experts across the globe, with offices in the United States, Grand Cayman, Ireland, Poland, Bulgaria, Luxembourg, the Philippines, and Australia. We've earned numerous accolades, including Top Overall Administrator, along with #1 rankings for providing alternative asset services in Accounting, Technology, Client Service, Investor Services, Alternative Fund Expertise, Reporting, and Regulatory Expertise.
The Product and Portfolio Support Team provide around the clock coverage for the creation, deployment, and upkeep of enterprise-wide Extract-Transform-Load (ETL) mappings. Key responsibilities include writing and maintaining Python-based Jupyter notebooks, designing workflows that ingest and transform incoming vendor and client files, and migrating legacy Excel logic into robust Python code.
This role involves transitioning legacy operations to more efficient and modern systems, while working with multiple business, technical and support teams for the development and maintenance of critical ETL mappings. They will use analytical skills to process and understand data, answer business questions, and be able to work independently and as part of a distributed global team.
The role offers the chance to author new guidelines, best-practice playbooks, and root-cause analysis procedures whenever incidents arise. On top of the day-to-day support tasks and ongoing long-term projects, team members will contribute to short-term projects for internal initiatives or cross-functional business units. The engineer will support process automation, data extraction, and customized solutions across various business units. Moreover, the candidate will be able to learn about the financial services/hedge fund industry.
Job Responsibilities
- ETL Development - Design, build, test, and evolve ETL pipelines using Python and Jupyter notebooks.
- Data Transformation - Convert raw data streams from multiple external sources into formats suitable for ingestion by proprietary applications.
- Documentation - Produce and maintain clear, detailed documentation for both new and existing ETL processes.
- Support & Incident Response - Deliver rapid, SLA-compliant assistance for tickets and incidents, with the ability to rapidly push fixes to production when needed.
- Continuous Improvement - Keep up-to-date with industry best practices, tools, and emerging technologies relevant to ETL and data engineering, and apply them to the team's workflows.
- Communication - Translating complicated problems and processes into streamlined solutions for various internal audiences, including senior management.
- Bachelor's degree in Computer Science, Information Systems, or equivalent professional experience.
- Strong proficiency in Python; experience with SQL and Bash is also required.
- Solid knowledge of data-science libraries such as Pandas, NumPy, and SciPy.
- Advanced Excel skills, including complex formula construction.
- Ability to read and interpret XML schemas and understand XML-based workflows.
- Experience and knowledge using AWS technologies including Kibana and APM for troubleshooting.
- Deep grasp of object-oriented programming, design patterns, and core software engineering concepts.
- Experience in agile software development, release and change management, and frequent deployments into production environments.
- Experience in the financial services industry and some knowledge of financial products is a plus.
- Excellent written and verbal communication skills in English.
- All qualifications are equally important; the ideal candidate will blend technical expertise with a proactive, service-oriented mindset.
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