Sr Data Engineer
IntegriChain5 months ago
Remote, United States or Philadelphia, PA, USASenior
Responsibilities
- Define enterprise data integration, consolidation, MDM integration, and data platform design patterns.
- Design, build, optimize, and operate Snowflake databases, schemas, tables, views, semantic layers, pipelines, and stored procedures.
- Build Reltio MDM ingestion, extraction, cross-reference, golden-record, survivorship, validation, reconciliation, and publishing workflows.
- Develop reliable ELT pipelines and reusable transformation models using dbt or comparable tooling and Python automation.
- Implement data quality, freshness, lineage, auditability, observability, logging, exception handling, dependency management, restartability, and incremental loading.
- Optimize Snowflake performance and costs through workload management, warehouse sizing, query profiling, clustering, monitoring, and cost allocation.
- Design enterprise analytical, operational, MDM, semantic, AI-ready, and reporting data models, including historical tracking and versioning patterns.
- Partner with Data Science, Product, Engineering, MDM, DevOps, Security, SRE, and business stakeholders to align data solutions and engineering standards.
- Collaborate on deployment automation, environment promotion, operational monitoring, and runbooks for data pipelines.
Requirements
- 10+ years of production experience in data engineering, database engineering, analytics engineering, or data platform development.
- Strong hands-on Snowflake experience covering architecture, performance tuning, security design, cost optimization, cost tracking, data sharing, and multi-environment deployments.
- Strong SQL and PL/SQL-style development experience with complex transformations, stored procedures, performance tuning, and large-scale processing.
- Python experience for automation, API integration, file handling, validation, metadata processing, or operational tooling.
- Experience with ETL/ELT tools; dbt experience is strongly preferred.
- Experience designing enterprise data models, curated and semantic layers, reusable data products, and integration patterns across applications, APIs, files, cloud storage, MDM platforms, and analytical systems.
- Understanding of MDM concepts including golden records, crosswalks/XREFs, match/merge, survivorship, hierarchies, entity relationships, stewardship, and data quality.
- Experience translating MDM or business requirements into source-to-target mappings, transformation logic, validation, and downstream consumption patterns.
- Experience implementing data quality, lineage, auditability, observability, and operational monitoring in data pipelines.
- Ability to work directly with cross-functional stakeholders, explain design tradeoffs, and drive alignment.
- Comfort operating as a hands-on senior individual contributor while influencing strategy and engineering standards.
- Preferred experience with Reltio MDM, life sciences or healthcare data, HIN, DEA, NPI, NCPDP, 340B/PHS, 844, 852, 867, chargebacks, gross-to-net, government pricing, PBR, or UBR datasets.
- Preferred experience with Airflow, Dagster, dbt Cloud jobs, cloud-native schedulers, Azure or AWS object storage, Terraform, Git-based development, infrastructure as code, AI-ready data architecture, feature stores, ML datasets, semantic models, or AI/ML pipeline enablement.
- Snowflake SnowPro, Reltio, dbt, or equivalent cloud/data engineering certification is preferred.
Benefits
- Excellent and affordable medical benefits.
- Flexible Paid Time Off and other non-medical perks.
- More than 700 free learning and development courses for employees.
- Mission-driven work focused on improving patients' lives.
- The posting does not state a work arrangement or office schedule.
About IntegriChain
IntegriChain provides a SaaS commercialization and revenue optimization platform for biopharma manufacturers, integrating data, software, and managed services to manage market access, payer contracting, patient services, and distribution analytics. Its ICyte platform unifies key commercial, financial, and operational data and is used by more than 250 manufacturers. Founded in 2005 and headquartered in Philadelphia, the company is privately held and backed by Nordic Capital.