Data Engineer

Independence Pet Group•New York, NY

11d•Hybrid

About The Position

Independence Pet Holdings is a corporate holding company established in 2021, managing a diverse portfolio of pet health brands and services. The IDEA (IPH Data & Enterprise Analytics) organization is responsible for building and operating the data platform, governance framework, and analytics capabilities that power decision-making across all brands. The team seeks a Data Engineer to play a critical role in shaping IPH’s data ecosystem, building platforms and pipelines for smarter decisions across analytics, product, and operations. This role requires technical excellence, a collaborative mindset, and experience in pet insurance or similar consumer-facing industries. The Data Engineer will design scalable, high-performance data solutions, ensure reliability, quality, and accessibility, foster cross-team partnerships, mentor peers, and champion best practices.

Requirements

3 years building and scaling cloud-based data platforms and pipelines.
Strong SQL and Python skills, with a focus on automation, performance, and reliability.
Experience with large-scale datasets, structured and unstructured.
Hands-on experience with modern data stack tools (dbt, Airflow, Fivetran, Databricks) and streaming/event-driven systems (Kafka, Kinesis).
Solid experience with AWS data services and ELT/ETL workflows.
Proficiency in CI/CD, Git, and infrastructure-as-code.
Proven ability to lead projects, influence stakeholders, and mentor others.

Nice To Haves

Experience designing data platforms at scale in a high-growth or startup environment.
Familiarity with customer-centric tools like Segment, Stripe, Salesforce, or mParticle.
Experience supporting analytics, machine learning, or personalization initiatives with robust data foundations.
Knowledge of data privacy and compliance best practices (e.g., GDPR, CCPA).
Prior contributions to open-source projects, internal data tooling, or technical blogs/presentations.

Responsibilities

Design, build, and scale cloud-based data platforms and pipelines (batch and streaming) to support analytics, product, and operational use cases.
Own critical data workflows, ensuring reliability, performance, and quality across the data ecosystem.
Implement modern data solutions using tools like dbt, Databricks, ELT frameworks, and other cloud platforms (AWS, Snowflake).
Apply best practices in CI/CD, Git, testing, monitoring, and infrastructure-as-code.
Collaborate effectively with cross-functional teams, balancing technical rigor with strong interpersonal skills to translate business needs into scalable, accessible data solutions.