Data Analyst, BLR

Key Responsibilities

Workflow Automation & Data Engineering

• Analyse data patterns across fund accounting, investor, portfolio, and transaction datasets to identify automation opportunities.
• Build and maintain automated workflows that surface the right data to the right process at the right time, reducing manual intervention.
• Develop SQL queries, stored procedures, views, and data extraction routines to power operational workflows.
• Optimise data pipelines for performance, reliability, and scalability.

API & Reporting Infrastructure

• Help design and build report providers and data services that can be called via APIs, enabling other systems and workflows to consume reporting outputs programmatically.
• Develop and maintain recurring and ad hoc reports for operations, finance, and management teams.
• Validate data accuracy and ensure consistency across fund accounting systems and downstream applications.
• Collaborate with stakeholders to translate reporting requirements into reusable, API-accessible technical solutions.

Vendor Application Integration

• Build lightweight wrappers and integrations around vendor applications (e.g. fund accounting platforms such as LemonEdge, Geneva, or Investran) to extend their functionality and connect them to internal workflows.
• Develop data import/export processes and system integrations that support straight-through processing across the operational stack.
• Work with internal teams and vendors to troubleshoot system issues and implement practical fixes.
• Support system enhancements, configuration changes, and process improvements as the platform evolves.

Operations Partnership & Straight-Through Processing

• Engage with wider operations teams to understand their day-to-day pain points and manual bottlenecks.
• Translate operational requirements into data and automation solutions that facilitate straight-through processing.
• Document business processes, technical solutions, and data flows to support knowledge sharing and audit requirements.
• Support data governance, compliance, and control frameworks.

Required Skills & Experience

• Bachelor's degree in Computer Science, Information Systems, Finance, Mathematics, or a related field.
• Solid SQL skills — you can write complex queries, stored procedures, and views without hand-holding.
• 1-3 years of experience in a data analyst, data engineer, or similar technical role.
• Demonstrable interest in automation — you look for patterns in repetitive work and want to eliminate them.
• Comfort working with APIs — either consuming them or thinking about how to expose data through them.
• Strong analytical and problem-solving mindset with attention to data quality.
• Good communication skills; able to translate between technical and non-technical stakeholders.

Preferred Qualifications

• Exposure to financial markets and an understanding of financial instruments is helpful, but we are equally interested in candidates with strong technical and analytical skills who are keen to learn the domain.
• Familiarity with fund accounting concepts (NAV, capital calls, distributions) or a genuine desire to learn them.
• Experience with scripting languages such as Python or PowerShell for automation.
• Experience integrating or wrapping third-party applications via APIs or middleware.
• Exposure to ETL processes, data warehousing, or data platform concepts.
• Experience with reporting or visualisation tools such as Power BI or Tableau.
• Hands-on experience with fund accounting platforms such as Geneva, Investran, or LemonEdge is a strong plus.

What Success Looks Like

• Manual, repetitive operational tasks are progressively automated — operations teams spend less time on data wrangling and more on judgement.
• Report providers and data services are accessible via APIs, enabling downstream systems and workflows to consume outputs without manual extraction.
• Vendor applications are seamlessly integrated into internal workflows through wrappers and integrations you have built.
• Straight-through processing rates improve across key operational workflows as a direct result of your contributions.
• Operations teams see you as a trusted technical partner who understands their workflows and can translate operational challenges into practical data, reporting, and automation solutions.
• You have developed a strong understanding of the asset classes we service and the fund accounting principles that underpin them—including NAV, capital calls, distributions, and investor allocations—allowing you to build solutions that are both technically robust and operationally meaningful.

Alchelyst is a client solutions and infrastructure partner for private markets asset managers. Purpose-built for the expanding demands and sophistication of global private markets, the firm offers a comprehensive managed service offering that can support GPs, private wealth funds and investors. Alchelyst has offices in the US, Ireland, UK, Luxembourg and India.

We are looking for a curious, technically minded Data Analyst with strong SQL skills and a passion for solving operational problems with data. You'll use SQL to analyze complex datasets, build automated workflows, and develop reporting and integration solutions, working at the intersection of fund accounting, data engineering, and systems integration. Partnering closely with operations teams, you'll help reduce manual effort, improve data quality, and enable straight-through processing through practical, scalable technology solutions.