Senior Data Engineer (Databricks)

Opis oferty

As a Senior Data Engineer, you will play a key role in designing, building, and scaling our clients’ cloud data platforms. You’ll work closely with technical and business stakeholders, influence architecture decisions, and drive best engineering standards across teams.
Expect cutting-edge cloud environments (Azure-first, with cross-cloud exposure), Databricks, Spark, robust CI/CD, and high-impact data solutions used across international organizations.

You'll join a team of passionate engineers who value technical excellence, collaboration, and continuous growth.

Why Join Us

At Cloudfide, we engineer solutions where data truly becomes an accelerator for innovation. We build and evolve large-scale Big Data and cloud-native platforms for global clients, including leaders in retail and the Fortune 500.
We process massive, complex datasets, operate fully in the cloud ecosystem, and work with the latest technologies, including AI, ML, MLOps, and modern data architectures.

Our projects have measurable, real‑world impact - from enhancing customer experiences at scale to empowering data-driven decision-making in high‑visibility global organizations.
As we continue to grow, you’ll have the opportunity to shape solutions, mentor others, drive architecture decisions, and take ownership of strategic initiatives.

Here's why you'll love Cloudfide

Benefits:

• MyBenefit platform / Multisport
• Enel‑Med private medical care
• Professional Growth:
• Annual 2,000 PLN development budget
• Access to e‑learning platforms
• Real opportunities to expand responsibility and lead initiatives - most of our Leads come from internal promotions
• As the company continuously grows, you get real opportunities to expand your responsibilities, explore new areas, and even take ownership of your own initiatives.
• Work Environment:
• Long-term cooperation: UZ or B2B (we value stable, lasting relationships)
• Remote-first, work from anywhere in the world (workation)
• Flexible hours & strong focus on work-life balance
• Collaboration with top engineers you can truly learn from
• Flat structure - every voice counts, and you help shape the company
• Culture & Integration:
• Company-wide trips (including international ones)
• Team integration budgets
• Open communication and supportive, passionate teams

Equal opportunities

CLOUDFIDE is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Wymagania

What We’re Looking For

• 4+ years of hands-on experience as a Data Engineer or in a closely related engineering role.
• 2+ years experience working with cloud platforms - we operate primarily in Azure, but AWS/GCP experience is equally valuable.
• Strong Python skills - ability to write maintainable, production-ready code in distributed data environments.
• Advanced SQL proficiency and experience with relational databases (SQL Server, PostgreSQL, etc.).
• Expertise in DWH data modeling, ETL/ELT architectures, and modern data design patterns (Lakehouse preferred).
• Solid understanding of cloud architecture, networking fundamentals, security, APIs, and scalable systems.
• Experience working with large-scale, high-volume datasets.
• Strong ownership mindset, creativity, and openness to innovation.
• Ability to operate autonomously and drive initiatives in dynamic, evolving cloud projects.

Nice to Have

• Experience with Databricks, Apache Spark, PySpark (big advantage).
• Hands-on knowledge of Apache Airflow or other orchestration tools.
• Experience with Azure DevOps or GitHub Actions for CI/CD.
• Familiarity with infrastructure as code (Terraform/Bicep).
• Exposure to AI/ML pipelines or MLOps environments.

Zakres obowiązków

• Designing and implementing scalable, production-grade data pipelines, data models, and data processing frameworks in cloud environments.
• Leading the technical design of cloud data architectures, contributing to standards, guidelines, and long-term platform strategy.
• Driving best practices in data engineering: quality assurance, lineage, observability, testing, automation, documentation.
• Optimizing data workflows for performance, cost efficiency, and reliability across distributed systems.
• Collaborating closely with clients and senior stakeholders to understand requirements, propose solutions, and communicate technical decisions.
• Working with CI/CD pipelines, infrastructure-as-code, and automation (DataOps) to streamline deployments and operations.
• Integrating data solutions with BI, ML, and application layers across diverse client environments.
• Mentoring mid-level engineers, supporting them in technical growth (without formal line management).
• Staying up-to-date with emerging technologies and proposing innovations to enhance platform capabilities.