Overview
We are partnering with a fast-growing SaaS business to hire a Lead Data Engineer to help shape and scale their modern data and analytics platform. This is a hands-on leadership role where you will guide a small team, own core data pipelines, and influence platform architecture while remaining close to the technology.
Key Responsibilities
- Lead, mentor, and develop a small team of data engineers and analysts, setting technical direction and establishing best practices.
- Own the end-to-end data lifecycle, from ingestion to analytics delivery, building and operating robust data pipelines using Databricks, Spark, and Delta Lake.
- Partner with product, engineering, and other cross-functional teams to deliver on the data roadmap, creating trusted datasets, dashboards, and APIs for both internal and external customers.
- Drive improvements in data quality, reliability, governance, and observability across the platform.
- Support and enhance CI/CD processes, automated testing, and cloud operations to ensure a scalable and resilient data infrastructure.
Required Skills & Experience
- Proven experience leading or mentoring data engineers, preferably within a SaaS or product-focused environment.
- Strong hands-on proficiency with the Databricks ecosystem, including Spark and Delta Lake.
- Expert-level skills in Python and SQL for data manipulation, pipeline development, and analysis.
- Solid experience with a major cloud platform (Azure is highly preferred).
- Excellent communication and collaboration skills, with a proven ability to work effectively with cross-functional teams.
Nice-to-Have
- Experience with data orchestration tools (e.g., Airflow, Dagster).
- Familiarity with Infrastructure as Code (IaC) principles and tools like Terraform.
- Knowledge of BI and data visualization tools (e.g., Power BI, Tableau).