Sr Manager, Data Engineering

Clarus Technology

New York (NY)

On-site

USD 150,000 - 230,000

Full time

14 days+

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Benefits offered by this job

Comprehensive full medical, dental and

vision insurance

Basic life insurance at no cost to the

employee

Company-paid short-term and long-term

disability

12 weeks of 100% paid parental leave

Health Savings Account (HSA)

Flexible Spending Accounts (FSA)

Retirement savings plan

Personal paid time off

Paid holidays and company-wide welfare

day off

Paid time off to volunteer at nonprofi

t organizations

Pet-friendly office environment

Commuter benefits

Group pet insurance

On-the-job training and skills develop

Employee Assistance Program (EAP)

Job summary

Clarus Technology in New York seeks a Senior Manager, Data Engineering to shape strategy, architecture, and execution of a modern data platform. You will drive ingestion, MDM, data quality, and platform engineering at scale, partnering with Engineering, Product, Analytics, and business leaders.

You will lead a team of data engineers, establish data governance, and champion lakehouse concepts, CI/CD, and DataOps to deliver trusted data assets for the company’s next growth phase in a highly

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, or related field.
10+ years in data engineering, data platform development, or related disciplines.
2+ years leading technical teams, mentoring engineers, or serving in a technical leadership capacity.
Deep experience with Azure cloud data platforms, including Azure Databricks, ADLS Gen2, Azure Data Factory, Event Hub, and related services.
Strong experience building modern data platforms, lakehouse architectures, and distributed data processing solutions.
Experience developing and implementing MDM solutions and enterprise data models.
Expertise with SQL, Python, Spark, and modern data engineering frameworks.
Experience building and supporting both batch and real-time data processing pipelines.
Strong understanding of data governance, metadata management, data quality, and security best practices.
Experience implementing CI/CD pipelines, DevOps practices, and infrastructure automation.
Excellent communication skills with the ability to influence technical and non-technical stakeholders.
Experience in healthcare, insurance, pet health, or other highly regulated industries is a plus.
Experience with entity resolution, probabilistic matching, or customer data platforms is a plus.

Responsibilities

Define and execute the roadmap for data engineering capabilities aligned with business and product priorities.
Design, build, and optimize scalable batch and real-time data ingestion frameworks using Azure Databricks, ADLS Gen2, and Azure-native technologies.
Establish reusable data engineering patterns, orchestration standards, and platform best practices.
Drive reliability, observability, performance optimization, and cost efficiency of data pipelines and infrastructure.
Lead the strategy and implementation of Master Data Management (MDM) capabilities across key business domains.
Define and govern trusted data assets and golden records for critical business entities including customers, products, providers, and partners.
Partner with business, product, and analytics stakeholders to ensure consistent and trusted enterprise data.
Develop scalable approaches for entity resolution, matching, taxonomy management, and hierarchical data modeling.
Champion modern lakehouse architecture principles and modular data design.
Establish robust data quality frameworks, monitoring, SLAs, and operational support processes.
Ensure alignment with enterprise governance, security, privacy, and regulatory requirements.
Lead, mentor, and grow a team of data engineers while fostering a culture of ownership, collaboration, and continuous improvement.
Contribute directly to architecture decisions, technical design, and critical implementation efforts when needed.
Drive agile delivery, sprint planning, and engineering best practices across the team.
Establish CI/CD standards, testing strategies, and DataOps best practices to support platform scalability and reliability.

Skills

Azure Databricks

ADLS Gen2

Azure Data Factory

SQL

Python

Spark

Data Modeling

Data Governance

CI/CD

DevOps

Leadership

Mentoring

Cloud Architecture

Education

Bachelor's degree in CS/Engineering/IT

10+ years data engineering experience

Tools

Git

Airflow

Terraform

CI/CD tooling

Job description

At Clarus, we are harnessing intelligence to propel pet health toward a brighter, smarter, and more connected future. A future where information flows freely across caregivers and care environments, insights are more instant and actionable, and financial decisions are empowered.

Role Overview

We are seeking a Senior Manager, Data Engineering to lead the strategy, architecture, and execution of Clarus' modern data platform. You will build and scale foundational data capabilities across data ingestion, master data management (MDM), data quality, and platform engineering. You will partner with Engineering, Product, Analytics, and business leaders to establish trusted, high‑quality data assets and deliver a data platform capable of supporting Clarus' next stage of growth.

Key Responsibilities

Define and execute the roadmap for data engineering capabilities aligned with business and product priorities.
Design, build, and optimize scalable batch and real‑time data ingestion frameworks using Azure Databricks, ADLS Gen2, and Azure‑native technologies.
Establish reusable data engineering patterns, orchestration standards, and platform best practices.
Drive reliability, observability, performance optimization, and cost efficiency of data pipelines and infrastructure.
Lead the strategy and implementation of Master Data Management (MDM) capabilities across key business domains.
Define and govern trusted data assets and golden records for critical business entities including customers, products, providers, and partners.
Partner with business, product, and analytics stakeholders to ensure consistent and trusted enterprise data.
Develop scalable approaches for entity resolution, matching, taxonomy management, and hierarchical data modeling.
Champion modern lakehouse architecture principles and modular data design.
Establish robust data quality frameworks, monitoring, SLAs, and operational support processes.
Ensure alignment with enterprise governance, security, privacy, and regulatory requirements.
Lead, mentor, and grow a team of data engineers while fostering a culture of ownership, collaboration, and continuous improvement.
Contribute directly to architecture decisions, technical design, and critical implementation efforts when needed.
Drive agile delivery, sprint planning, and engineering best practices across the team.
Establish CI/CD standards, testing strategies, and DataOps best practices to support platform scalability and reliability.

Qualifications

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
10+ years of experience in data engineering, data platform development, or related disciplines.
2+ years of experience leading technical teams, mentoring engineers, or serving in a technical leadership capacity.
Deep experience with Azure cloud data platforms, including Azure Databricks, ADLS Gen2, Azure Data Factory, Event Hub, and related services.
Strong experience building modern data platforms, lakehouse architectures, and distributed data processing solutions.
Experience developing and implementing Master Data Management (MDM) solutions and enterprise data models.
Expertise with SQL, Python, Spark, and modern data engineering frameworks.
Experience building and supporting both batch and real‑time data processing pipelines.
Strong understanding of data governance, metadata management, data quality, and security best practices.
Experience implementing CI/CD pipelines, DevOps practices, and infrastructure automation.
Excellent communication skills with the ability to influence technical and non‑technical stakeholders.
Experience in healthcare, insurance, pet health, or other highly regulated industries is a plus.
Experience with entity resolution, probabilistic matching, or customer data platforms is a plus.