Sr Manager, Data Engineering

Independence Pet HoldingsChicago, MA
Onsite

About The Position

At Clarus, we are harnessing intelligence to propel pet health towards a brighter, smarter, more connected future. A future where information flows freely across caregivers & care environments, insights are more instant and actionable, and financial decisions are empowered. For us, that future starts by fundamentally changing how pet insurance operates. We’re engineering systems that decomplexify coverage and facilitate reimbursement, so more pets can get the care they deserve. Our team of pet industry veterans and passionate pet people come from across the tech and health continuums. Together, we’re openly challenging industry convention in service of creating totally new possibilities. Which is why our culture is built on the values of curiosity, entrepreneurship, humility and fierce collaboration. Role Overview We are seeking an experienced and hands-on Senior Manager, Data Engineering to lead the strategy, architecture, and execution of Clarus' modern data platform. This role will be responsible for building and scaling foundational data capabilities across data ingestion, master data management (MDM), data quality, and platform engineering. As a growing organization, Clarus values leaders who can balance strategic thinking with hands-on execution. The ideal candidate thrives in fast-paced environments, enjoys solving complex data challenges, and is excited to build scalable data foundations that enable products, analytics, operational workflows, and business decision-making. This role will partner closely 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.

Requirements

  • 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.

Nice To Haves

  • 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.

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)
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