Job Summary
 

At Alto Pharmacy, the Data Engineering team plays a crucial role in driving the company’s mission to transform the pharmacy industry. This team is responsible for designing and building scalable data pipelines, as well as managing ETL processes, data visualization, and metadata platforms such as Fivetran, Snowflake, dbt, Looker, and DataHub, all of which power business analytics and decision-making. In addition, the team handles data transformations using Apache Spark and manages the machine learning platform (Kubeflow) that automates and optimizes pharmacy operations.

Alto's Data Engineers also manage AWS components to support data platforms running in AWS EKS clusters, with Terraform handling IAM, S3, SNS, SQS, and other essential services. Furthermore, they are tasked with data integrations across healthcare networks, drug manufacturers, and various partnerships.

Our goal is to make high-quality data accessible to everyone at Alto to accelerate decision-making and improve our products. We are seeking a Senior Data Engineer with extensive experience, a customer-centric mindset, and a strong sense of ownership to join our team. Your expertise will empower us to make data-driven decisions that enhance patient care and drive innovation in the pharmacy space.

Job Description
 

Accelerate Your Career as You

Data Pipeline Development:

• Design, develop, and maintain robust data pipelines to collect, process, and store large volumes of data.

• Ensure data quality, integrity, and security across all stages of the data lifecycle.

• Implement data ingestion, transformation, and loading (ETL/ELT) processes with Python and DBT.

Data Infrastructure and Management:

• Manage and optimize data storage solutions, including data warehouses and databases.

• Implement and maintain data governance practices and policies.

• Support and enhance existing data processing platforms deployed in AWS EKS. 

• Ensure compliance with data privacy regulations (e.g., HIPAA).

Cross-Functional Collaboration:

• Work closely with software engineers, product managers, and business analysts to understand data requirements and deliver solutions.

• Provide technical guidance and mentorship to junior engineers and data scientists.

• Communicate complex technical concepts and results to non-technical stakeholders.

Continuous Improvement:

• Stay up-to-date with the latest advancements in data engineering and machine learning.

• Experiment with new tools and technologies to enhance our data infrastructure and ML capabilities.

• Contribute to the development of best practices and standards for data engineering and machine learning.

A Bit About You

Minimum Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

• 7+ years of production data engineering experience

• Strong technical skills in python, SQL, and data modeling

• Experience using and tuning data processing frameworks such as Apache Spark, Hadoop, or similar.

• Experience with data warehouses, E(LT/TL) tools, and cloud services

• Experience with cloud platforms such as AWS, GCP, or Azure.

• Strong problem-solving skills and attention to detail.

• Strong sense of ownership over your work

• Comfortable working at startup pace and focus

Preferred Qualifications: 

• Experience in the healthcare or pharmaceutical industry.

• Knowledge of healthcare data standards and privacy regulations (e.g., HIPAA).

• Familiarity defining and implementing security and data access policies

• Experience with big data technologies and distributed computing.

• Familiarity with DevOps practices and tools (e.g., Docker, Kubernetes).

• Experience with AWS, GCP, Azure cloud development and deployment

• Demonstrated experience improving data governance, accuracy, and latency

Additional Information
 

Additional Physical Job Requirements

Physical requirements for this role include the ability to work at a computer termi