Sr Manager, Data Engineering

Clarus Technology; Chicago (IL); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Comprehensive health insurance

Parental leave (12 weeks)

HSA

FSA

Retirement savings plan

Paid time off

Paid holidays

Volunteer time off

Pet-friendly office

Commuter benefits

Group pet insurance

On‑the‑job training

Employee Assistance Program

Job summary

Clarus Technology is seeking a Senior Manager of Data Engineering to lead the strategy, architecture, and execution of Clarus' modern data platform in Chicago. You will build scalable data ingestion, MDM, data quality, and platform engineering capabilities, partnering with Engineering, Product, Analytics, and business leaders to deliver trusted data assets and support growth.

You will guide a team of data engineers, drive CI/CD, and champion DataOps while aligning with governance, security, and

Qualifications

• 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.

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 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 ownership and collaboration.
• Contribute to architecture decisions, technical design, and critical implementation efforts when needed.
• Drive agile delivery, sprint planning, and engineering best practices.
• Establish CI/CD standards, testing strategies, and DataOps best practices to support platform reliability.

Skills

Leadership

SQL

Python

Spark

Data governance

Data quality

Communication

Security best practices

Observability

CI/CD

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field

Tools

Azure Databricks

ADLS Gen2

Azure Data Factory

Event Hub

CI/CD pipelines

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.

Benefits

• 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 wellness day off
• Paid time off to volunteer at nonprofit organizations
• Pet‑friendly office environment
• Commuter benefits
• Group pet insurance
• On‑the‑job training and skills development
• Employee Assistance Program (EAP)