Senior Data Analyst - Analytics and Automation

About Welo Global  Welo Global is a leader in multilingual AI, technology, and content solutions serving over 2,000 clients in 300 languages. The company combines globally scaled multilingual infrastructure, including a network of over 500,000 linguists and domain experts, with advanced NLP, computational linguistics, and best-in-class compliance backed by seven ISO certifications. Welo Global’s five brands—Welocalize (multilingual content and localization services for global enterprises), Park IP (intellectual property and patent translation services for law firms and corporate legal teams), Welo Life Sciences (regulated language and compliance-aligned content solutions for pharmaceutical, biotech, and medical device organizations), Adapt (multilingual performance-led digital marketing agency), and Welo Data (multilingual data generation, evaluation, and human data infrastructure for AI systems)—serve distinct customer segments with purpose-built expertise, fit-for-purpose solutions, and supporting technology. weloglobal.com  About the Role We're hiring a technically strong Senior Data Analyst to help modernize how our FP&A organization uses data, analytics, and automation. This is an embedded Finance role: you'll report directly to the FP&A Director and work side by side with her day to day while partnering closely with our central Data Analytics and Data Engineering teams on infrastructure, standards, and complex technical problems. It's a hands-on execution role for someone who builds. Financial and operational data at Welocalize lives across multiple systems - Workday Financials, Adaptive Planning, Salesforce, a Redshift data warehouse, Power BI, and years of Excel workbooks carrying critical processes. Much of it doesn't connect cleanly, and a lot of institutional knowledge lives in undocumented spreadsheets, manual processes, and Power Queries rather than any system of record. You might start with a complex, years-old Excel workbook and a simple prompt: “This is how we do this today.” Your job isn't to automate the workbook as-is - it's to understand its purpose, trace its logic to source, figure out what users actually need, and design something better: a rebuilt pipeline, a SQL/Python replacement, a driver-based view, an exception-monitoring workflow, or an AI-assisted tool. We're just starting to build out an FP&A AI repository - documentation, business logic, and workflows meant to let AI reliably execute FP&A processes, not just answer one-off questions - and you'll partner with us to determine its direction. This role is a deliberate combination of three things: 1. Fluency with data itself - the ability to query, shape, and manipulate data directly. 2. An engineering mindset - building automated, repeatable systems (workflows and dashboards that run and refresh on their own, integrations across tools) rather than one-off analysis, and knowing how to scope and coordinate real pipeline or data mart work with Data Engineering. 3. An investigative instinct - the ability to look at data and figure out what it's telling us, not just execute a report exactly as specified.