Sr Data Engineer

Stack

Responsibilities

• ▹Partner with Data Science leadership to rationalize and consolidate the enterprise data landscape across products and platforms
• ▹Define reusable data integration patterns for batch, micro-batch, and near-real-time data exchange
• ▹Design and build data pipelines that load source data into Reltio MDM and extract mastered outputs for downstream use
• ▹Engineer integration patterns for HCO Master data, including party/entity, address, identifier, hierarchy, relationship, match/merge, and survivorship/golden record outputs
• ▹Develop validation and reconciliation processes comparing source, Reltio-mastered, and Snowflake data
• ▹Design Snowflake database, schema, view, and semantic-layer patterns for performance and maintainability
• ▹Optimize Snowflake workloads (clustering, warehouse sizing, query profiling, workload isolation)
• ▹Implement Snowflake cost tracking and optimization practices
• ▹Build reliable ELT pipelines using dbt or comparable tooling
• ▹Develop Python-based automation for API integration, file processing, and metadata management
• ▹Design logical and physical data models for enterprise analytical, MDM, and AI-ready datasets
• ▹Process and optimize large data volumes in Snowflake using efficient SQL and Snowflake Scripting

Requirements

• ▹10+ years of experience in data engineering, database engineering, or data platform development in production environments
• ▹Strong hands-on Snowflake experience (architecture, performance tuning, security design, cost optimization)
• ▹Hands-on experience with ETL/ELT tools; dbt experience strongly preferred
• ▹Strong SQL and PL/SQL-style development experience, including complex transformations, stored procedures, and performance tuning
• ▹Python experience for data automation, API integration, data validation, and metadata processing
• ▹Experience designing enterprise data models, curated data layers, semantic layers, and reusable data products
• ▹Experience with data integration patterns across enterprise applications, APIs, files, cloud storage, operational systems, MDM, and analytical platforms
• ▹Working understanding of Master Data Management concepts (golden records, crosswalks/XREFs, match/merge, survivorship, hierarchies, entity relationships, stewardship)
• ▹Experience partnering with MDM, product, or business teams to translate mastering requirements into source-to-target mappings, transformation logic, and validations

About the company

IntegriChain is the data and application backbone for market access departments of Life Sciences manufacturers. More than 250 manufacturers rely on its ICyte Platform to orchestrate commercial and government payer contracting, patient services, and distribution channels. Headquartered in Philadelphia, PA (USA), with offices in Ambler, PA (USA), Pune, India, and Medellín, Colombia.