Remote Analytics Engineer: Real-World Data Pipelines

United States Digital Space LLC; United States; Remote; USD 175,000 - 200,000; Full time

Job summary

Arcadia is seeking a remote data pipeline engineer who will own end-to-end RWD delivery pipelines. You will write production-grade PySpark and dbt models, replace legacy Snowflake scripts, and configure endpoints as code for partner data delivery.

You will partner with platform engineering, implement HIPAA de-identification rules, and ensure data quality through dashboards and validation tests. This is a high-ownership role with growth as the LS organization scales.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
• 5+ years of hands-on data engineering experience with production pipelines and cloud data infra.
• Experience with life sciences RWD data (claims, EHR, clinical) is a plus.

Responsibilities

• Author and maintain dbt models and PySpark transformation jobs replacing ad-hoc scripts with governed, tested code.
• Design and implement delivery endpoint configurations as code—target, cadence, cohorts, incremental refresh.
• Write production-grade Python and PySpark for data transformation and validation automation.
• Configure and maintain AWS S3 delivery paths and Iceberg table structures for partner data.
• Collaborate with platform engineering to extend Argo Workflows for automated delivery.
• Implement HIPAA de-identification rules in pipeline code and coordinate updates.

Skills

dbt & PySpark development

Data pipeline ownership

Strong communication with partners

Problem solving & debugging

Education

Bachelor's or Master's in CS/Data Science or related

Tools

dbt-Spark

PySpark

Snowflake

AWS S3

Argo Workflows

Git/GitHub

Job description

Arcadia is seeking a remote data pipeline engineer who will own end-to-end RWD delivery pipelines. You will write production-grade PySpark and dbt models, replace legacy Snowflake scripts, and configure endpoints as code for partner data delivery.

You will partner with platform engineering, implement HIPAA de-identification rules, and ensure data quality through dashboards and validation tests. This is a high-ownership role with growth as the LS organization scales.