Data Engineering Lead / Manager Location: 100 % Remote Employment Type: Long-term Contract/ FTE
Position Overview
We are looking for an experienced Data Engineering Lead / Manager to guide our data platform team, design scalable data architecture, and drive modern engineering best practices. In this role, you will balance technical leadership with hands-on infrastructure management, working closely with cross-functional partners to build secure, reliable, and high-performance data systems.
Key Responsibilities
Team & Project Leadership: Manage and mentor a team of data engineers, setting technical standards, conducting code reviews, and prioritizing delivery roadmaps.
Data Platform Architecture: Architect, scale, and maintain enterprise data lakes and warehouses using Databricks or Snowflake.
Cloud Infrastructure: Design and optimize cloud data pipelines on AWS or Azure, ensuring cost efficiency, high availability, and performance.
Infrastructure as Code (IaC): Automate environment provisioning, deployments, and infrastructure management using Terraform.
Containerization & Orchestration: Deploy, scale, and manage containerized data applications and orchestration workflows on Kubernetes.
Governance & Reliability: Enforce data quality standards, security policies, access controls, and robust CI/CD pipelines across all environments.
Required Qualifications
Experience: 6+ years in Data Engineering, with at least 2+ years in a team lead or managerial
Data Stack: Proven expertise in Databricks (Delta Lake, PySpark) or Snowflake.
Cloud Platforms: Hands-on proficiency with AWS (S3, EKS, Glue, IAM) or Azure (ADLS, AKS, Data Factory).
DevOps & IaC: Strong production experience writing modular infrastructure code with Terraform.
Containerization: Hands-on experience managing and deploying clusters via Kubernetes.
Core Skills: Fluency in Python, SQL, advanced data modeling, and modern CI/CD