Data Engineer

Job description

At HedgeServ, we’re redefining what’s possible in fund administration. With more than $700 billion in assets under administration, we partner with the world’s most forward-thinking investment managers – across private equity, private credit, endowments, hedge funds and more – to deliver seamless, tech-enabled solutions that drive performance. 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. Job Description: The Data Engineer supports the Product and Portfolio Support Team in the development, deployment, and maintenance of enterprise-wide Extract-Transform-Load (ETL) processes. This role helps design, build, and support data pipelines that transform information from external vendors and clients into formats suitable for internal applications. The role also includes developing and maintaining Python-based solutions, including Jupyter notebooks, and supporting the migration of legacy processes into standardized, scalable code. The position contributes to the transition from legacy operations to modern data platforms and works closely with business, technical, and support teams to maintain critical ETL workflows. It also requires analysing and interpreting data to support operational and business needs. The role combines operational support with project-based work, including internal initiatives and cross-functional collaboration. Responsibilities include contributing to process documentation, automation solutions, and continuous improvement across data engineering practices. The position operates within a distributed global team and follows defined service level requirements, including coverage aligned with U.S. business hours. Job Responsibilities: Design, build, test, and maintain ETL pipelines using Python and Jupyter notebooks to support data processing requirements. Transform raw data from external sources into structured formats suitable for internal systems. Produce and maintain ETL documentation to ensure clarity, consistency, and auditability. Provide support for incidents and service requests in line with defined service levels, including deploying fixes where required. Contribute to continuous improvement by applying relevant tools, technologies, and best practices in data engineering. Translate technical requirements and data issues into structured solutions for internal stakeholders. Support process automation and the development of data extraction and transformation solutions across business units. Contribute to internal standards, guidelines, and root cause analysis processes. 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. Job Requirements: Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent practical experience. Experience developing ETL processes or working with data pipelines. Experience in environments involving data transformation, automation, or software development. Proficiency in Python, including experience with Jupyter notebooks. Experience with SQL and Bash scripting. Knowledge of data processing libraries such as Pandas, NumPy, and SciPy. Advanced Excel skills, including complex formula development. Ability to interpret XML schemas and work with XML-based processes. Experience with AWS technologies, including monitoring and troubleshooting tools such as Kibana and APM. Understanding of software engineering principles, including object-oriented programming and design patterns. Familiarity with agile development, release management, and production deployment processes. 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; we are looking for a blend of technical expertise with a proactive, service‑oriented mindset. Please note that this role requires working during U.S. business hours.