Senior Data Engineer

Careers at Keel

Keel Infrastructure is a publicly traded energy and digital infrastructure company that develops and owns data centers and power assets across North America.

At Keel, you’re not just joining a company, you’re helping build the infrastructure behind the future of compute.

Why Keel

We’re at the intersection of energy and technology, two industries transforming in real time.

The work is complex. The pace is fast. The impact is real.

You’ll be part of a team that values:

• Ownership— we take responsibility and follow through
• Collaboration— we work across teams, functions, and borders
• Curiosity— we ask questions and keep learning
• Endurance— we build for the long term
  
  

What It Feels Like to Work Here

• Fast-moving, high-growth, and hands-on
• Smart, driven people solving real challengestogether
• Work that directly supports AI and next-generation infrastructure
• Room to grow, stretch, and take on more
  
  

What We Offer

• Competitive salary, bonusand equity opportunities
• Comprehensive health and wellness benefits
• Retirement savings with company contribution
• Employee referral program
  
  

We are currently looking for a Senior Data Engineer to join our team.

Compensation:

Expected Salary: $120,000 - $170,000 USD

What You Can Expect from This Role

The Senior Data Engineer will play a critical role in designing, building, and operating Keel’s next-generation data platform. This role is responsible for architecting and implementing a modern Data Lakehouse, establishing a data classification program aligned with a new Data Loss Prevention (DLP) initiative, and partnering closely with business and technical stakeholders to understand, classify, and govern data across the organization.

This position requires strong technical depth in data engineering and architecture, combined with the ability to translate business needs, compliance requirements, and security objectives into scalable and well-governed data solutions.

Key Responsibilities

Data Platform & Lakehouse Architecture

• Design, implement, and maintain a scalable Data Lakehouse architecture supporting analytics, reporting, and advanced workloads.
• Define data ingestion, transformation, and storage patterns for structured, semi-structured, and unstructured data.
• Establish best practices for data modeling, partitioning, performance optimization, and cost efficiency.
• Ensure high availability, reliability, and data quality across the data platform.
  
  

Data Classification & DLP Enablement

• Lead the design and implementation of a data classification framework aligned with Keel’s security, compliance, and business requirements.
• Partner with Cybersecurity and Compliance teams to support the rollout of a Data Loss Prevention (DLP) program.
• Identify, tag, and manage sensitive data (e.g., financial, operational, personal, or regulated data) throughout the data lifecycle.
• Ensure data classification is embedded into ingestion pipelines, storage layers, and access controls.
  
  

Stakeholder Engagement & Data Assessment

• Work closely with business stakeholders, IT, Security, and Compliance teams to:
• Assess existing and new data sources.
• Understand data usage, criticality, and sensitivity.
• Define classification levels, retention rules, and access requirements.
• Translate stakeholder needs into technical data models, pipelines, and governance controls.
• Act as a trusted advisor on data architecture, data governance, and data protection topics.
  
  

Data Governance & Security

• Implement data access controls, lineage, and auditability in alignment with internal policies and regulatory requirements.
• Support SOX, ITGC, and other compliance-driven data controls as applicable.
• Contribute to the definition of data standards, naming conventions, and documentation.
  
  

Operations & Continuous Improvement

• Monitor and optimize data pipelines for performance, reliability, and cost.
• Troubleshoot and resolve complex data-related issues across environments.
• Continuously evaluate new tools, technologies, and patterns to improve the data ecosystem.
• Mentor junior engineers and contribute to internal knowledge sharing.
  
  

What We Are Looking For

• 7+ years of experience in data engineering or data platform roles.
• Proven experience designing and implementing data lake and/or lakehouse architectures.
• Strong experience with data ingestion, ETL/ELT pipelines, and large-scale data processing.
• Solid understanding of data classification, data governance, and data security concepts.
• Experience collaborating with security or compliance teams on data protection initiatives (e.g., DLP, data privacy).
• Ability to communicate complex technical concepts clearly to non-technical stakeholders.
  
  

More Details

• Work schedule: Monday-Friday, New York City office, 4 days on-site, 1 WFH
• Job type: Full Time, Permanent
  
  

NYC: $120,000 USD - $170,000 USD