Data Engineer/Assoc. Commercial Data Architect

Scorpion Therapeutics; Pennsylvania; On-site; USD 90,000 - 130,000; Full time

Job summary

Scorpion Therapeutics seeks a data engineering/analytics professional to translate business needs into scalable data architectures and trusted metrics. You will partner with sales, product strategy, market access, and finance to design data models and governance frameworks.

Responsibilities include documenting BRDs and data dictionaries, building lakehouse patterns with Databricks on Azure, and owning commercial data domains such as customers and sales.

Qualifications

• 3+ years in data roles (data engineering/analytics engineering/BI or similar).
• Bachelor’s degree in a technical field.
• Strong data modeling and SQL; modern data platforms (Databricks preferred; Azure Synapse/Snowflake acceptable).
• Knowledge of commercial app architecture (CRM, MDM, reporting platforms).
• Hands-on SQL and cloud platform experience.

Responsibilities

• Translate business needs into data architecture; partner with sales, product strategy, market access, and finance to design data models.
• Document solutions (BRDs, functional specs, data dictionaries, ERDs, process flows) for technical and business audiences.
• Design usable, scalable data solutions aligned with KPIs; support a business-facing data layer for consistent, trusted metrics and self-service analytics.
• Use Databricks and Azure to build Lakehouse patterns, medallion architectures, and structured SQL Server schemas.
• Own commercial data domains: customers, sales effectiveness, master data, specialty pharmacy; ensure consistency, lineage, and reliability.
• Structure data for dashboards, forecasting pipelines, and performance tracking.
• Support integration/governance of pharmaceutical data sources (e.g., IQVIA Xponent, 867 data, specialty pharmacy feeds).
• Bridge technical and business teams; validate requirements and clarify ambiguity.
• Uphold data quality and governance via standards, naming conventions, and early pipeline quality controls.

Skills

Data modeling

SQL

Databricks

Azure Synapse

CRM

MDM

Reporting

Education

Bachelor’s degree in a technical field

Tools

Databricks

Azure Synapse

Snowflake

Job description

Key Responsibilities

• Translate business needs into data architecture; partner with sales, product strategy, market access, and finance to design data models.
• Document solutions (BRDs, functional specs, data dictionaries, ERDs, process flows) for technical and business audiences.
• Design usable, scalable data solutions aligned with KPIs; support a business-facing data layer for consistent, trusted metrics and self-service analytics.
• Use Databricks and Azure to build Lakehouse patterns, medallion architectures, and structured SQL Server schemas.
• Own commercial data domains: customers, sales effectiveness, master data, specialty pharmacy; ensure consistency, lineage, and reliability.
• Structure data for dashboards, forecasting pipelines, and performance tracking.
• Support integration/governance of pharmaceutical data sources (e.g., IQVIA Xponent, 867 data, specialty pharmacy feeds).
• Bridge technical and business teams; validate requirements and clarify ambiguity.
• Uphold data quality and governance via standards, naming conventions, and early pipeline quality controls.

Qualifications / Required Skills

• 3+ years in data roles (data engineering/analytics engineering/BI or similar).
• Bachelor’s degree in a technical field.
• Strong data modeling and SQL; modern data platforms (Databricks preferred; Azure Synapse/Snowflake acceptable).
• Knowledge of commercial app architecture (CRM, MDM, reporting platforms).
• Hands-on SQL and cloud platform experience.

Qualifications / Preferred Skills

• Exposure to ETL/ELT, star vs. normalized models, and lakehouse patterns.
• Experience working with business stakeholders.
• Familiarity with pharmaceutical data (Xponent Plantrak, 867, specialty pharmacy, marketing, finance, customer data).
• Experience creating BRDs, functional specs, data dictionaries, or process diagrams.
• Proven alignment of data initiatives with business outcomes; clear communication and strong problem-solving.