At Cloudfide, we build and scale solutions where data becomes a strategic asset and a catalyst for innovation. We engineer large-scale Big Data and cloud-native platforms for international clients, including leading companies in retail and the Fortune 500.
We work entirely in the cloud ecosystem, process massive real-time datasets, and leverage the latest technologies, including Databricks, Spark, AI/ML, and modern MLOps frameworks.
Our projects drive meaningful impact - improving global digital products and powering high-visibility business decisions.
As we continue to grow, you’ll have the opportunity to shape architectures, influence technical direction, mentor engineers, and lead complex initiatives.
Opportunity Overview
As a Lead Data Engineer, you’ll take ownership of designing and scaling end‑to‑end cloud data platforms.
You’ll work with clients, architects, engineers, and cross-functional partners to define robust technical solutions and ensure excellence across delivery.
Expect modern cloud environments (Azure-first), full Databricks ecosystem, strong CI/CD, and impactful projects used across global organizations.
responsibilities :
Designing and owning cloud-native data architectures (lakehouse, distributed processing, data platforms).
Leading technical decision-making: setting standards, defining patterns, reviewing solutions, and guiding long-term architecture.
Building and optimizing scalable, production-ready data pipelines and large-scale processing systems.
Working closely with clients and senior stakeholders to understand business needs and translate them into technical direction.
Identifying architectural gaps and leading modernization & optimization initiatives.
Setting direction for technical roadmaps and ensuring platform scalability, reliability, and maintainability.
Providing technical leadership to engineers: mentoring, reviewing code, guiding design decisions (formal leadership experience not required).
Supporting integrations with BI, ML, and platform engineering teams.
Bringing in new technologies, methodologies, and innovations to elevate technical capabilities.
requirements-expected :
4+ years of hands-on experience as a Data Engineer, working on complex or large-scale cloud data environments.
Proven technical leadership experience - formal or informal - such as guiding other engineers, owning components, leading delivery, or driving architecture.
Strong experience with cloud platforms - we use Azure, but AWS/GCP experience is equally valuable.
