Lead Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead, mentor, and nurture the Data Engineering team.

• Set clear expectations regarding performance, quality, and ownership.

• Oversee team priorities, workload, and delivery in accordance with business goals.

• Provide technical expertise and oversight for architecture, design, and production readiness.

• Act as an escalation point for intricate technical, data quality, and delivery issues.

• Design, develop, and maintain scalable data pipelines, integrations, warehouses, and supporting infrastructure.

• Define engineering standards for data architecture, modeling, reliability, performance, and maintainability.

• Stay actively involved in the development and resolution of complex or business-critical technical challenges.

• Enhance automation, tooling, monitoring, and engineering methodologies.

• Establish technical direction and priorities for the Data Engineering team.

• Collaborate with Finance and other stakeholders to convert data requirements into effective solutions.

• Assess technologies, processes, and architectural strategies.

• Convey technical strategy, risks, recommendations, and infrastructure needs to leadership.

• Support team and organizational goals while performing assigned responsibilities and special projects.

⛳️ Requirements

• Over 7 years of relevant data engineering experience.

• More than 2 years of experience leading, supervising, or providing technical guidance to others.

• A Bachelor's degree in Computer Science, Data Engineering, or a related field, or equivalent technical training or professional experience.

• Extensive experience in designing, building, and maintaining data pipelines, ETL/ELT processes, data warehouses, and associated infrastructure.

• Advanced SQL proficiency.

• Strong programming skills in Python, Java, Scala, or a similar language.

• Deep understanding of data architecture, modeling, scalability, performance, reliability, and data quality practices.

• Experience with modern cloud data platforms, orchestration frameworks, and data processing technologies.

• Capability to remain technically hands-on while leading and developing a team.

• Strong business insight and ability to translate business needs into practical technical solutions.

• Excellent communication and stakeholder management skills across both technical and non-technical audiences.

• Preferred: Experience with AWS, Azure, or Google Cloud Platform.

• Preferred: Familiarity with Airflow, dbt, or similar orchestration and transformation tools.

• Preferred: Experience with Kafka or Spark.

• Preferred: Experience with infrastructure-as-code and CI/CD methods for data environments.

• Preferred: Experience in building, scaling, or advancing a Data Engineering function.

🏝️ Benefits

• Option to work from home.

• Traditional climate-controlled office setting.

• Reasonable accommodations for individuals with disabilities.

• At-will employment.