Senior Snowflake Data Engineer

In your day-to-day, you will:
- Architect, design, and develop high-performance, maintainable, and secure Snowflake-based data platforms.
- Build and optimize robust data pipelines, including batch and near-real-time ingestion frameworks using best-in-class tools (e.g., dbt, Snowpipe, Streams & Tasks).
- Implement advanced data transformations and models (star/snowflake schemas, SCDs, time-travel) using SQL, dbt, and Python.
- Collaborate with analytics, business intelligence, and data science teams to deliver trustworthy, scalable, and business-aligned data assets.
- Drive the adoption of software engineering best practices in the data lifecycle: CI/CD pipelines, modularization, versioning, testing, and documentation.
- Ensure end-to-end data governance, security, privacy, and lineage tracking are implemented across the Snowflake ecosystem.
- Contribute to the data architecture roadmap, influencing choices on tooling, modularity, and long-term scalability.
- Provide technical mentorship to junior engineers and participate in the selection and onboarding of future team members.

You might be a great fit if you have:

-Minimum 10 years of experience in data engineering, with at least 6 years in Snowflake development in enterprise-scale environments.

Strong proficiency in:

- SQL (Snowflake dialect, query tuning, UDFs, stored procedures).
- dbt (Data Build Tool) for modular transformations and testing.
- Python for orchestration and complex transformations.
- Optional but valued: JavaScript, Scala, or Shell scripting.

-Proven experience in Snowflake-specific capabilities: roles & RBAC, resource monitors, data sharing, materialized views, zero-copy cloning, dynamic masking, time travel, tasks, and streams.
- Deep understanding of data warehousing principles, data modeling (3NF, dimensional, data vault), and ELT/ETL architecture patterns.
- Expertise in CI/CD for data environments, preferably with tools such as GitHub Actions, Azure DevOps, or GitLab CI.
- Experience with orchestration frameworks (e.g., Airflow, Prefect, Dagster) and monitoring tools (e.g., Monte Carlo, Great Expectations).
- Familiarity with modern data catalogs, governance tools, and data quality frameworks.

Leadership Potential:

-Demonstrated ability to lead technical initiatives, mentor teams, and influence architectural decisions.
- Capable of translating strategic business needs into scalable, production-ready data solutions.

Educational Background & Certifications:

-Bachelor’s or Master’s degree in a relevant field: Computer Science, Engineering, Mathematics, Physics, or other STEM disciplines.
- Strong foundation in algorithms, distributed computing, and database theory.

Preferred certifications:

- Snowflake SnowPro Core Certification (required).
- SnowPro Advanced: Architect or Data Engineer (highly desirable).
- Certifications in dbt, AWS/GCP/Azure Data Engineering, or equivalent.
- Continuous learner mindset with a demonstrated commitment to staying up to date with modern data technologies.

We're offering:
- Hybrid model: 2 remote days per week.
- A key role in shaping the future of Fluidra’s data platform architecture.
- Collaborative, diverse, and innovative environment focused on impact and learning.
- Opportunities for leadership growth and participation in cross-functional strategic initiatives.
- Competitive compensation, training resources, and flexible work arrangements.
- Flexible working hours.