Senior Data Engineer

Keel Infrastructure

$120K — $170K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 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.
  • Ability to communicate complex technical concepts clearly to non-technical stakeholders.

Responsibilities

  • Design, implement, and maintain a scalable Data Lakehouse architecture for analytics and advanced workloads.
  • Define data ingestion, transformation, and storage patterns for varied data types.
  • Establish best practices for data modeling, optimization, and cost efficiency.
  • Lead the design and implementation of a data classification framework for security and compliance.
  • Partner with Cybersecurity and Compliance teams for DLP program rollout.
  • Identify and manage sensitive data throughout its lifecycle and ensure proper tagging.
  • Monitor and optimize data pipelines for performance and cost efficiency.

Benefits

  • New York City office with a hybrid work schedule of 4 days on-site and 1 day remote.
  • Permanent full-time position with a dynamic team environment.
Full Job Description
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-$170,000 USD

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