【Flexii】Data Analyst

About Flexii

At Flexii, we are building an on-demand work-matching platform to unlock human potential across Asia. We connect businesses with a verified, flexible workforce, allowing people to work on their own terms and get paid almost instantly. We are a fast-growing, seed-funded startup and are looking for engineers who want to build the future of the gig economy.

About the Role

As we scale user activity, matching quality, and operational insights, we're looking for a versatile Data Engineer / Analyst to own our end-to-end data capabilities. This is a hybrid hands-on role combining data and data. You'll work closely with our frontend, backend, and product teams in a collaborative startup environment, helping drive product improvements and business decisions through data.

Key Responsibilities

Data Infrastructure & Engineering

• Design, build, and maintain scalable ETL/ELT pipelines to collect, clean, and transform data from our web portal, mobile app, APIs, and other sources into a reliable data warehouse.
• Manage and evolve our data warehouse primarily in Google BigQuery, including schema design, partitioning/clustering for cost/performance, and migration toward hybrid SQL/NoSQL setups for growing analytical workloads.
• Implement data quality checks, monitoring, and alerting to ensure trustworthy data for analysis and product features.
• Facilitate the setup of data tracking (event logging, user behavior, matching events) using tools like Google Analytics, custom event tracking, or similar.
• Collaborate with backend engineers on data-related topics (e.g. API instrumentation, database optimization in PostgreSQL, planning for NoSQL adoption like Bigtable and/or MongoDB).

Data Analysis & Modeling

• Perform exploratory data analysis to uncover insights on user behavior, retention, churn, worker/employer satisfaction, and platform economics, etc.
• Create dashboards/reports in Looker Studio (or similar tools like Tableau/Power BI if needed) to track KPIs and support product/operations decisions.
• Build and iterate on scoring models using NLP techniques, embeddings/vector models (e.g. text similarity for job-worker fit, review sentiment), and machine learning to improve our service quality.
• Evaluate results from A/B tests or quasi-experiments to measure impact of product changes (e.g. new matching algorithms, UI tweaks).
• Translate business questions into data queries and deliver clear, actionable recommendations to product, operations, and leadership teams.

Additional Scope (as the data function grows)

• Support data needs for product experimentation and growth initiatives.
• Document data models, pipelines, and business logic for team knowledge sharing.
• Stay up-to-date with new data tools and best practices; suggest improvements to our stack as we scale.
• Help define data governance basics (e.g. access controls, PII handling) in a startup context.

Requirements

• 2+ years of experience in data engineering, analytics engineering, or a closely related role.
• Strong proficiency in SQL (preferably PostgreSQL) and hands-on experience with BigQuery (or similar data warehouses like Redshift, Snowflake).
• Hands-on experience in building ETL/ELT processes (e.g. using Cloud Functions, Dataflow, Cloud Composer, Airflow, or similar).
• Hands-on experience in Looker Studio (or similar tools like Looker, Tableau, Power BI) for visualization and reporting.
• Hands-on experience in vector embeddings or NLP libraries (e.g. Gemini API Embeddings, Hugging Face sentence-transformers, scikit-learn).
• General awareness of software development practices (APIs, version control/Git, backend/frontend concepts) to collaborate effectively with engineering teams.
• Excellent communication skills — able to explain technical concepts and insights to non-technical stakeholders.
• Proactive, self-motivated mindset suited to an emerging startup (comfortable wearing multiple hats and iterating quickly).

Nice-to-Haves

• Experience with GCP ecosystem beyond BigQuery (e.g. Vertex AI, Cloud Functions).
• Exposure to ML model deployment.
• Exposure to NoSQL database.
• Prior work in marketplace platforms, gig economy, HR-tech, or matching/recommendation systems.

Please note: Due to the high volume of applications, we unfortunately can't get back to every one of you and only successful applicants will be contacted. When you share your details with us, we consider this as consent for us to use your data during the application process. At the moment, Flexii is not in a position to sponsor work visas so you have to be eligible to work legally in the country where we are hiring.