Data Engineer

Summary

Join Workleap's Data Engineering team as a Staff Developer to design, build, and maintain scalable and secure data pipelines. You will lead the modernization of the ELT stack, collaborating with various teams to ensure data accessibility, reliability, and security. This role requires a high level of technical autonomy, deep architectural thinking, and hands-on Snowflake expertise. You will mentor junior team members and participate in architecture decisions to improve scalability and cost-efficiency. The team focuses on delivering new data features at scale, enforcing data security and governance, and leading Snowflake adoption. This position offers the opportunity to work on a next-generation product-oriented data platform.

Requirements

• 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

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

Preferred Qualifications

• 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