Top Tech Jobs & Startup Jobs

Build scalable analytical solutions and dashboards using Power BI, Databricks, SQL and Python. Design KPI frameworks, perform statistical analysis and experimentation, ensure data quality and governance, partner with Product/Commercial/Tech teams, and communicate insights to stakeholders.

Support product roadmap for TaDa Delivery by identifying customer problems, writing requirements and user stories, partnering with design and engineering, prioritizing work, running discovery and experiments, tracking metrics, coordinating launches, and iterating to improve customer experience and business outcomes.

Create executive-ready dashboards and visualizations, leverage AI/ML and automation to build data products, manage commercial master data, synthesize large datasets into scalable models, collaborate with local analytics and engineering teams, communicate commercial results to senior leadership, own and govern Commercial Performance data assets, and deliver ad-hoc analyses on pricing, market share, and volume performance.

Support BEES Pay payment operations globally: monitor payment flows, identify and resolve anomalies and failed transactions, perform end-to-end reconciliations, track settlement cycles and escalate discrepancies, and improve/automate processes to increase reliability.

Lead product development for BEES Fintech Core, defining and prioritizing backend services and APIs that enable payments. Partner with engineering and architects to translate requirements, align stakeholders, monitor metrics, and support delivery of scalable payment integrations across systems.

Support internal communications and culture by developing and executing comms plans, writing internal messaging and presentations, coordinating stakeholders, creating toolkits and FAQs, and partnering with People teams to amplify culture, engagement, and change initiatives.

The Global Manager, Growth & Planning will oversee strategic planning, market engagement, and commercial projects to drive growth and enhance business performance.

Own product direction for ML platform capabilities across the end-to-end ML lifecycle. Set vision and roadmap, define standards and tooling, drive adoption with data science and engineering teams, deliver templates/CLIs/workflows, and improve model deployment, observability, and operational practices to enable scalable, reliable ML solutions.

The Data Engineer will implement ETL/ELT solutions, design data pipelines, ensure data security, and optimize data processing systems. Responsibilities include data transformation and compliance collaboration.

Design and implement highly available, fault-tolerant infrastructure and SRE best practices. Collaborate with development teams to ensure reliability, automate operations, build monitoring/observability, lead incident response and post-incident analysis, and evaluate/adopt tooling for cloud, container, and GitOps environments.