Data Engineering Lead / Manager

Daman; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Daman is seeking an experienced Data Engineering Lead/Manager to guide the data platform team, design scalable architecture, and implement modern engineering practices. The role blends technical leadership with hands-on infrastructure management in a cross-functional setting.

You will build secure, reliable, high-performance data systems using Databricks or Snowflake, on AWS or Azure, and drive IaC with Terraform and Kubernetes-based deployments.

Qualifications

• At least 2–4 years in a team lead or managerial role.
• Proven Databricks (Delta Lake, PySpark) or Snowflake expertise.
• Hands-on AWS (S3, EKS, Glue, IAM) or Azure (ADLS, AKS, Data Factory).
• Strong DevOps experience with Terraform.
• Hands-on Kubernetes cluster management.
• Fluency in Python and SQL, with modern CI/CD practices.

Responsibilities

• Lead and mentor a team of data engineers, set technical standards, conduct code reviews, and prioritize delivery roadmaps.
• Architect, scale, and maintain enterprise data lakes and warehouses using Databricks or Snowflake.
• Design and optimize cloud data pipelines on AWS or Azure, ensuring cost efficiency, high availability, and performance.
• Automate environment provisioning, deployments, and infrastructure management using Terraform.
• Deploy, scale, and manage containerized data applications and orchestration workflows on Kubernetes.
• Enforce data quality standards, security policies, access controls, and robust CI/CD pipelines across all environments.

Skills

Team leadership

Databricks

Snowflake

Python

SQL

AWS

Azure

Terraform

Kubernetes

Data modeling

CI/CD

Tools

Databricks

Snowflake

AWS

Azure

Terraform

Kubernetes

Job description

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: Required in Data Engineering, with at least 2-4 years in a team lead or managerial capacity.
• 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 practices.