Description

Lead a team of developers to build and maintain scalable data pipelines and cloud data architectures.

Responsibilities

• Develop and maintain scalable data pipelines using Azure and PySpark to extract, load, and transform data into cloud warehouses.
• Provide technical guidance, conduct code reviews, and oversee quality assurance and performance optimization.
• Design and optimize data storage solutions, database schemas, and data models while enforcing governance and security guidelines.
• Format and distribute custom data extracts via APIs, SFTPs, and other mediums.
• Collaborate with stakeholders to define project scope, deliverables, and technical feasibility for complex projects.

Required Skills

• 10+ years of professional experience in data engineering or technical leadership.
• Expertise with Azure Stack including Azure Data Lake (ADL), Blob Storage, Azure Data Factory, and Databricks (ADB).
• Proficiency in Python and PySpark for ETL/ELT processes.
• Strong experience with MySQL and on-premises Microsoft SQL Server.
• Experience ingesting data into cloud-native data warehouses.
• Ability to troubleshoot database connectivity and optimize data retrieval using SQL.
• Experience defining data quality protocols and enterprise reference architecture.
• Strong verbal and written communication skills for technical and non-technical stakeholder collaboration.

Preferred Skills

• Experience with DataRobot, Domino Data Labs, Salesforce MC, or Veeva CRM.
• Familiarity with Snowflake Warehouse and statistical concepts like regression analyses or hypothesis testing.
• Knowledge of healthcare marketing analytics, claims data, and medical coding sets (ICD, HCPCS, NPIs).

Key Skills

Education

Any Graduate