Arine
Overview
Join to apply for the
Staff Data Engineer - Data Operations
role at
Arine .
Based in San Francisco, Arine is a rapidly growing healthcare technology and clinical services company with a mission to ensure individuals receive the safest and most effective treatments for their unique and evolving healthcare needs.
We combine cutting edge data science, machine learning, AI, and deep clinical expertise to introduce a patient-centric view to medication management, and develop and deliver personalized care plans on a massive scale for patients and their care teams.
Arine is committed to improving the lives and health of complex patients that have an outsized impact on healthcare costs. Backed by leading healthcare investors and collaborating with top healthcare organizations and providers, we deliver recommendations and facilitate clinical interventions that lead to significant, measurable health improvements for patients and cost savings for customers.
The Role This position offers a fast-paced environment with a strong team of diverse engineers that are central in building Arine\'s data operations infrastructure. You will have the opportunity to have a direct impact on the scalable ingestion and operational architecture that supports our internal data platform. Working alongside analytics engineers who focus on dbt transformations, you will own the critical EL (Extract-Load) infrastructure that feeds our medallion architecture, ensuring raw data flows from our platform sources into our staging layer where analytics engineers can build robust dbt models for our data science, machine learning/AI, and reporting teams.
Responsibilities
Architecting and implementing scalable data ingestion infrastructure from platform sources (RDS, DynamoDB) into Snowflake
Building event-driven data pipelines using tools like Kinesis, Airbyte, or other open-source ingestion frameworks that scale effectively
Designing systems that support our medallion architecture and enable smooth data flow into the staging layer
Creating configuration-driven, containerized toolsets that can be easily used and maintained by diverse engineering profiles
Collaborating with analytics engineers to ensure smooth data flow into the staging layer for dbt transformations
Implementing incremental data migration strategies for large-scale healthcare datasets
Building monitoring and alerting systems for data ingestion processes and pipeline health
Applying software engineering best practices including test-driven development and modular design to data infrastructure
Refactoring and rebuilding existing data ingestion processes to improve scalability and operational efficiency
Working with containerization technologies (Docker, Kubernetes) to create portable and maintainable data solutions
Supporting the migration to our staging → intermediate → marts medallion structure
Mentoring team members on data operations best practices and infrastructure design patterns
Qualifications
6+ years of professional experience in data engineering with focus on large-scale data ingestion and infrastructure
Strong experience with scalable data ingestion tools such as Kinesis, Airbyte, Kafka, or similar open-source solutions
Proven experience building event-driven ETL/ELT systems that move large datasets from operational databases (RDS, DynamoDB) to data warehouses (Snowflake)
Deep understanding of software engineering principles including test-driven development, loose coupling, single responsibility, and modular design
Experience with containerization technologies (Docker, Kubernetes) and building configuration-driven, maintainable systems
Understanding of medallion/layered data architecture patterns and experience supporting analytics engineering workflows
Experience with incremental data processing and change data capture (CDC) methodologies
Hands-on experience with cloud data infrastructure, particularly AWS services (S3, Kinesis, Lambda, Step Functions, RDS, DynamoDB)
Proven ability to build tools and systems that can be operated by diverse engineering profiles through configuration rather than code changes
Experience working with large healthcare datasets and understanding of data privacy and compliance requirements
Demonstrated ability to refactor and improve existing data infrastructure for better scalability and operational efficiency
Strong collaboration skills working with analytics engineers, data scientists, and ML engineers
Excellent verbal and written communication skills with ability to explain technical infrastructure concepts to diverse audiences
Passion for building robust, maintainable, and operationally excellent data systems
Remote Work Requirements
An established private work area that ensures information privacy
A stable high-speed internet connection for remote work
This role is remote, but you will be required to come to on-site meetings multiple times per year. This may be in the interview process, onboarding, and team meetings
Compensation The base salary range for this position is:
$165,000-180,000/year .
Job Requirements
Ability to pass a background check
Must live in and be eligible to work in the United States
Information Security and EEO All staff at Arine are expected to be part of its Information Security Management Program and undergo periodic training on Information Security Awareness and HIPAA guidelines. Each user is responsible to maintain a secure working environment and follow all policies and procedures. Upon hire, each person is assigned and must complete trainings before access is granted for their specific role within Arine.
Arine is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace where all employees are treated with fairness and respect. We do not discriminate on the basis of race, ethnicity, color, religion, gender, sexual orientation, age, disability, or any other legally protected status. Our hiring decisions and employment practices are based solely on qualifications, merit, and business needs. We encourage individuals from all backgrounds to apply and join us in our mission.
Check our website at
https://www.arine.io . This is a unique opportunity to join a growing start-up revolutionizing the healthcare industry!
Job Offers: Arine uses the arine.io domain and email addresses for all official communications. If you received communication from any other domain, please consider it spam.
Note to Recruitment Agencies: We appreciate your interest in finding talent for Arine, but please be advised that we do not accept unsolicited resumes from recruitment agencies. All resumes submitted to Arine without a prior written agreement in place will be considered property of Arine, and no fee will be paid in the event of a hire. Thank you for your understanding.
#J-18808-Ljbffr
Staff Data Engineer - Data Operations
role at
Arine .
Based in San Francisco, Arine is a rapidly growing healthcare technology and clinical services company with a mission to ensure individuals receive the safest and most effective treatments for their unique and evolving healthcare needs.
We combine cutting edge data science, machine learning, AI, and deep clinical expertise to introduce a patient-centric view to medication management, and develop and deliver personalized care plans on a massive scale for patients and their care teams.
Arine is committed to improving the lives and health of complex patients that have an outsized impact on healthcare costs. Backed by leading healthcare investors and collaborating with top healthcare organizations and providers, we deliver recommendations and facilitate clinical interventions that lead to significant, measurable health improvements for patients and cost savings for customers.
The Role This position offers a fast-paced environment with a strong team of diverse engineers that are central in building Arine\'s data operations infrastructure. You will have the opportunity to have a direct impact on the scalable ingestion and operational architecture that supports our internal data platform. Working alongside analytics engineers who focus on dbt transformations, you will own the critical EL (Extract-Load) infrastructure that feeds our medallion architecture, ensuring raw data flows from our platform sources into our staging layer where analytics engineers can build robust dbt models for our data science, machine learning/AI, and reporting teams.
Responsibilities
Architecting and implementing scalable data ingestion infrastructure from platform sources (RDS, DynamoDB) into Snowflake
Building event-driven data pipelines using tools like Kinesis, Airbyte, or other open-source ingestion frameworks that scale effectively
Designing systems that support our medallion architecture and enable smooth data flow into the staging layer
Creating configuration-driven, containerized toolsets that can be easily used and maintained by diverse engineering profiles
Collaborating with analytics engineers to ensure smooth data flow into the staging layer for dbt transformations
Implementing incremental data migration strategies for large-scale healthcare datasets
Building monitoring and alerting systems for data ingestion processes and pipeline health
Applying software engineering best practices including test-driven development and modular design to data infrastructure
Refactoring and rebuilding existing data ingestion processes to improve scalability and operational efficiency
Working with containerization technologies (Docker, Kubernetes) to create portable and maintainable data solutions
Supporting the migration to our staging → intermediate → marts medallion structure
Mentoring team members on data operations best practices and infrastructure design patterns
Qualifications
6+ years of professional experience in data engineering with focus on large-scale data ingestion and infrastructure
Strong experience with scalable data ingestion tools such as Kinesis, Airbyte, Kafka, or similar open-source solutions
Proven experience building event-driven ETL/ELT systems that move large datasets from operational databases (RDS, DynamoDB) to data warehouses (Snowflake)
Deep understanding of software engineering principles including test-driven development, loose coupling, single responsibility, and modular design
Experience with containerization technologies (Docker, Kubernetes) and building configuration-driven, maintainable systems
Understanding of medallion/layered data architecture patterns and experience supporting analytics engineering workflows
Experience with incremental data processing and change data capture (CDC) methodologies
Hands-on experience with cloud data infrastructure, particularly AWS services (S3, Kinesis, Lambda, Step Functions, RDS, DynamoDB)
Proven ability to build tools and systems that can be operated by diverse engineering profiles through configuration rather than code changes
Experience working with large healthcare datasets and understanding of data privacy and compliance requirements
Demonstrated ability to refactor and improve existing data infrastructure for better scalability and operational efficiency
Strong collaboration skills working with analytics engineers, data scientists, and ML engineers
Excellent verbal and written communication skills with ability to explain technical infrastructure concepts to diverse audiences
Passion for building robust, maintainable, and operationally excellent data systems
Remote Work Requirements
An established private work area that ensures information privacy
A stable high-speed internet connection for remote work
This role is remote, but you will be required to come to on-site meetings multiple times per year. This may be in the interview process, onboarding, and team meetings
Compensation The base salary range for this position is:
$165,000-180,000/year .
Job Requirements
Ability to pass a background check
Must live in and be eligible to work in the United States
Information Security and EEO All staff at Arine are expected to be part of its Information Security Management Program and undergo periodic training on Information Security Awareness and HIPAA guidelines. Each user is responsible to maintain a secure working environment and follow all policies and procedures. Upon hire, each person is assigned and must complete trainings before access is granted for their specific role within Arine.
Arine is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace where all employees are treated with fairness and respect. We do not discriminate on the basis of race, ethnicity, color, religion, gender, sexual orientation, age, disability, or any other legally protected status. Our hiring decisions and employment practices are based solely on qualifications, merit, and business needs. We encourage individuals from all backgrounds to apply and join us in our mission.
Check our website at
https://www.arine.io . This is a unique opportunity to join a growing start-up revolutionizing the healthcare industry!
Job Offers: Arine uses the arine.io domain and email addresses for all official communications. If you received communication from any other domain, please consider it spam.
Note to Recruitment Agencies: We appreciate your interest in finding talent for Arine, but please be advised that we do not accept unsolicited resumes from recruitment agencies. All resumes submitted to Arine without a prior written agreement in place will be considered property of Arine, and no fee will be paid in the event of a hire. Thank you for your understanding.
#J-18808-Ljbffr