Staff Developer in Data Engineering

Job Description 

At Workleap, we’re transforming how teams work by turning scattered knowledge into smart, actionable insights. Our AI-powered products surface the right information at the right time, across platforms and tools our customers use every day.

We’re looking for developers in data engineering who thrive on solving complex integration challenges and building secure, scalable pipelines to support a variety of analytics and AI use cases. Your work will enable governed, high-impact usage of data across our ecosystem.

You’ll collaborate with data engineers, data scientists, and app developers to ensure data is accessible, reliable, and protected, thus contributing to the foundations of a product that blends intelligence with control.

So, what will your new role look like?

Workleap is looking for a staff developer in data engineering to help shape and scale our next-generation product-oriented data platform.

This role calls for a high level of technical autonomy, deep architectural thinking, and hands-on expertise with Snowflake, which is central to our data strategy.

Responsibilities:

• Design, build, and maintain scalable and secure data pipelines across structured, semi-structured, and unstructured sources.
• Lead the modernization of our ELT stack, migrating from custom-built logic to managed, database-centric solutions.
• Collaborate with app developers, platform engineers, and data scientists to enable data-driven product features.
• Own and drive best practices in data modeling, processing, and observability.
• Leverage the full potential of Snowflake, including support for structured, semi-structured, and unstructured data, as well as capabilities such as streams, tasks, and secure data sharing.
• Ensure data quality, lineage, and security through rigorous automation, RBAC, data policies, and metadata management.
• Mentor junior and intermediate team members to elevate technical standards and practices.
• Participate in architecture decisions and continuously improve scalability and cost-efficiency.

What does your future team look like?   

As part of the Data Engineering team, you will be responsible for designing, building, and optimizing robust data pipelines that support analytics, AI/ML, and product-led data experiences across our SaaS applications.

You’ll work closely with app developers, data scientists, and platform engineers to ensure our data infrastructure is reliable, secure, and efficient – and most importantly, delivers value to our users.

What are the next challenges awaiting your team?   

• Delivering new data features at scale
• Enforcing end-to-end data security and governance
• Leading Snowflake adoption and ecosystem maturity
• Keeping pace with a rapidly evolving tech stack

Qualifications

• Proven experience in data engineering delivering production-grade pipelines, infrastructure, and data products.
• Deep, hands-on expertise with Snowflake, including performance optimization, data sharing, and native support for various data formats.
• Strong proficiency in SQL and Python, especially for analytical and automation purposes.
• Solid experience with dbt for data transformation, modeling, documentation, and testing.
• Familiarity with cloud platforms (preferably Azure) and containerized environments.
• Experience with resource provisioning and infrastructure-as-code tools (e.g., Terraform).
• Strong understanding of data warehousing and data lakes/lakehouses.
• Practical knowledge of data governance principles, RBAC, data access policies, and secure data design.
• Experience mentoring or technically leading other developers.
• Excellent communication skills and a collaborative mindset.
• Passion for scalable, maintainable, and evolvable data architectures.
• Experience with orchestration tools (Dagster, Airflow, etc.).
• Familiarity with Snowpark or Snowflake’s built-in ML/AI capabilities.
• Exposure to streaming platforms (Kafka, Redpanda) and event-driven architectures.
• Background in designing or evolving internal data platforms or developer-facing tooling.