Orchid Security– Senior Data Engineer

Description

With $36M seed funding, led by Team8 and IntelVC, customers from Fortune 500 companies, including Costco and Repsol, Orchid Security is already on an exciting journey to deliver the next infrastructure layer in the security space. Behind our platform stands advanced technologies such as Large Language Models (LLMs) allowing Orchid to deliver unprecedented insight and action for enterprise identity security.

This is a unique opportunity to be the first data engineer in the company and play a key role in shaping our data infrastructure from the ground up. You will take ownership of our data initiatives, working closely with engineering, product, and business stakeholders to ensure our data capabilities support and accelerate our growth.

Your Role Will Include:

• Leading the design, implementation, and optimization of our end-to-end data infrastructure, including ETL processes, data pipelines, and data warehousing solutions.
• Owning and managing the company’s BI/data infrastructure to support data-driven decision-making across all teams.
• Building and maintaining efficient and scalable data models, views, and reporting layers to provide actionable insights.
• Collaborating with cross-functional teams to understand business requirements and translate them into robust data solutions.
• Ensuring data quality, accuracy, and security across all systems and pipelines.
• Evaluating and integrating new data tools and technologies to enhance our data ecosystem.
• Mentoring and guiding teams on data best practices and driving a data-first culture within the

Requirements

• 5+ years of experience as a Data Engineer, with a strong track record of designing and implementing scalable data solutions.
• Proficiency in Snowflake, DBT, and PostgreSQL—a must.
• Experience with orchestration tools (Airflow, Prefect, Temporal)
• Strong experience in building and maintaining ETL/ELT pipelines using modern data stack tools.
• Hands-on experience with SQL performance tuning and query optimization.
• Solid understanding of data warehousing concepts, modeling techniques, and best practices.
• Experience with data visualization and BI tools (e.g., Tableau, Looker, or similar).
• Proficiency in Python for data processing and automation.
• Ability to work independently, take ownership, and drive projects from concept to completion.
• Excellent problem-solving skills and a proactive approach to identifying and addressing challenges.
• Strong communication skills with the ability to collaborate effectively with technical and non-technical stakeholders.

Advantages:

• Experience working in early-stage startups, dealing with rapid growth and evolving requirements.
• Familiarity with additional cloud data platforms and services (AWS, GCP, Azure).
• Experience implementing data governance and security best practices.