The Role
Leads the architecture, development, optimization, and governance of large-scale batch and streaming data pipelines and cloud data platforms. Establishes engineering standards, automation, CI/CD, data quality, monitoring, and security practices. Mentors engineers, drives architectural decisions, manages technical debt and risks, and collaborates with architecture, analytics, platform, product, and business stakeholders to deliver reliable enterprise data solutions.
Summary Generated by Built In
Work Flexibility: Hybrid
The Lead Data Engineer leads the design, development, and optimization of complex, high-scale data pipelines and platform solutions across the Data and Analytics organization. This role provides technical leadership, mentors junior engineers, and partners with Data Architecture, Analytics, and Platform teams to define engineering standards, drive best practices, and deliver reliable, well-governed data solutions that support enterprise analytics and reporting needs.
What you will do:
- Lead the architecture and optimization of scalable ETL/ELT pipelines, data models, and cloud-based data platforms to power enterprise analytics.
- Drive engineering excellence through automation, orchestration, CI/CD, performance tuning, and adoption of best practices across the data landscape.
- Establish robust data quality, governance, security, and monitoring frameworks to ensure reliable and trusted data solutions.
- Mentor engineering teams and collaborate with business, product, and architecture stakeholders to deliver high-impact, scalable data products.
- Expert in designing scalable batch and streaming data architectures, delivering high-performance and cost-efficient data solutions.
- Advanced proficiency in SQL, Python, Scala, and distributed processing frameworks with deep expertise in cloud data platforms.
- Strong technical leader who mentors engineers, drives architectural decisions, and translates complex concepts for diverse stakeholders.
- Proven ability to manage multiple priorities, mitigate risks, reduce technical debt, and deliver strategic outcomes with minimal oversight.
What you will need :
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related discipline required with 6-8 years of experience in data engineering, data platform development, or related technical roles.
- Advanced expertise in SQL, Python/Scala/Java, and cloud-based data engineering, with a proven track record of building scalable, production-grade data pipelines and optimizing modern data platforms.
- Strong technical leader with deep knowledge of data architecture and modeling, recognized for mentoring teams, driving design excellence, and managing stakeholders to deliver high-impact business outcomes.
- Deep experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse.
- Advanced experience with orchestration tools such as Apache Airflow, Azure Data Factory, or dbt at enterprise scale, and streaming/event-driven architectures such as Kafka, Kinesis, or Event Hubs.
- Strong background in CI/CD, infrastructure-as-code, and containerization (Docker/Kubernetes) for data platforms.
- Advanced knowledge of data modeling techniques (dimensional modeling, star schema, data vault) and metadata/data governance practices, knowledge of Data Lake, Lakehouse and Unity Catalogue Concepts, use of Tool’s AI features to bring efficiency in Coding and bug fixing
- Advanced cloud platform certification (AWS, Azure, or GCP Data Engineer/Architect track) preferred./ Snowflake, Databricks, or equivalent advanced data platform certification preferred.
Skills Required
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline
- 6-8 years of experience in data engineering, data platform development, or related technical roles
- Advanced expertise in SQL and Python, Scala, or Java
- Experience building scalable, production-grade data pipelines and optimizing modern data platforms
- Strong technical leadership, data architecture, data modeling, mentoring, design excellence, and stakeholder management experience
- Deep experience with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse
- Advanced experience with Apache Airflow, Azure Data Factory, or dbt at enterprise scale
- Experience with streaming and event-driven architectures such as Kafka, Kinesis, or Event Hubs
- Strong background in CI/CD, infrastructure as code, and containerization using Docker or Kubernetes
- Advanced knowledge of dimensional modeling, star schema, data vault, metadata, and data governance practices
- Knowledge of Data Lake, Lakehouse, and Unity Catalog concepts
- Advanced cloud platform certification in AWS, Azure, or GCP Data Engineer or Architect tracks
- Snowflake, Databricks, or equivalent advanced data platform certification
Inari Medical Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Inari Medical and has not been reviewed or approved by Inari Medical.
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Fair & Transparent Compensation — Pay is considered competitive for many roles, with employees described as 'extremely happy' with total compensation including pay, stock, equity, and benefits. Feedback suggests above‑average salary levels across departments contribute to strong pay sentiment.
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Healthcare Strength — Benefits include comprehensive medical, dental, and vision coverage, with 100% employer‑paid premiums for employees cited in multiple descriptions. Additional options like critical illness, accident, hospital indemnity, and wellness programs reinforce the healthcare offering.
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Leave & Time Off Breadth — Time off is characterized by unlimited PTO, cited as a top benefit by employees. Paid holidays and flexible hours are also referenced, expanding the range of time‑off options.
Inari Medical Insights
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The Company
What We Do
Inari Medical, Inc. is a commercial-stage medical device company focused on developing products to treat and transform the lives of patients suffering from venous diseases.
