Data Engineering Team Lead

Summary

Join Geoforce's growing team as a Data Engineering Team Lead! This player-coach role blends hands-on technical work with team leadership. You will guide the team in designing and implementing next-generation data infrastructure, contributing directly to critical projects. Strategic direction, alignment with business goals, and fostering a growth-oriented environment are key responsibilities. The ideal candidate is technically proficient and an empathetic leader, capable of inspiring a high-performing team. You'll be involved in various aspects, from senior engineering tasks to product collaboration and technical leadership. This role requires significant experience in data engineering and team leadership.

Requirements

• Hands-on experience with building and operating data pipelines, ETL frameworks, and data infrastructure in production environments
• Expertise in Airbyte, Fivetran, Snowflake, and Databricks for data warehousing, data integration, and analytics
• Strong proficiency in SQL and working with large datasets, with experience building data models for Looker and PowerBI
• Expertise in Apache Kafka for real-time data streaming and event-driven architectures
• Experience with Infrastructure as Code and configuration management tools like Terraform, Ansible, and monitoring tools like Datadog
• Proficient in Python, with experience in other languages like Scala
• Experience with containers and orchestration tools such as Docker and Kubernetes
• Strong understanding of data modeling, including data lakes, relational databases, NoSQL, and OLAP cubes
• 8+ years of experience as a hands-on data engineer, demonstrating deep technical expertise in building complex, scalable data solutions
• 3+ years of experience leading data engineering teams or initiatives, demonstrating strategic thinking, mentoring, and advising stakeholders
• Bachelor’s degree in Computer Science, Data Science, or a related field

Responsibilities

• Act as a player-coach by balancing technical responsibilities with team leadership
• Provide mentorship and support for engineers, while also taking development responsibility of key data engineering initiatives
• Lead the design, development, and deployment of highly scalable and reliable data infrastructure using modern tools like Snowflake, Databricks, and cloud-based services
• Continuously refine the data architecture to meet evolving business and technical needs
• Design, build, maintain, and optimize data pipelines and ETL processes using tools like Airbyte and Fivetran for efficient data ingestion, transformation, and storage
• Ensure these pipelines are robust, scalable, and production ready
• Work closely with cross-functional teams including data analysts, product managers, software engineers, and business stakeholders to understand data requirements and deliver high-value data solutions
• Utilize Looker and PowerBI to provide actionable insights and drive decision-making
• Oversee the management of data infrastructure using modern cloud-based environments (AWS preferred)
• Implement best practices for infrastructure as code, configuration management, and monitoring (e.g., Terraform, Ansible, Datadog)
• Proactively manage and mitigate technical debt within the data platform, balancing the need for innovation with system stability and scalability
• Drive innovation in data engineering by experimenting with new technologies, techniques, and tools
• Cultivate a culture of learning and continuous improvement within the team
• Establish and maintain data governance standards to ensure the integrity, consistency, and accuracy of data
• Implement techniques for monitoring data infrastructure reliability and correctness
• Take ownership of the operational reliability of data systems, including on-call support for critical data infrastructure components

Preferred Qualifications

• Familiarity with AI/ML pipelines and AWS services like SageMaker or Lambda for scalable model deployment
• A strong interest in driving data governance initiatives and ensuring data quality