Senior Data Engineer

Binariks is looking for a Senior Data Engineer to connect an emerging AI platform to large-scale healthcare and pharma data. The role will build the pipelines, curated facts and semantic models that feed both AI agents and a knowledge graph.

The project is an emerging AI decision-intelligence platform for pharmaceutical commercial teams, developed for a US healthcare data and analytics company. It turns daily specialty-pharmacy, hub, payer and clinical data into AI-generated recommendations that show why they were made and who acts on them, then measures whether they worked. The role will join a senior Binariks team working alongside the client's product and engineering teams on AWS.

What we are looking for:
5+ years in data engineering with a solid track record in client-facing environments
Strong practical experience architecting and running production environments on Databricks (Delta Lake, Unity Catalog, Workflows)
Proficiency in Python (PySpark) and advanced SQL for complex data transformations and high-performance querying (PostgreSQL / Amazon RDS)
Proven hands-on track record building robust batch and streaming architectures on AWS (experience with GCP is also considered)
Experience defining business metrics, data abstraction layers, or knowledge graph feeds
Deep understanding of data observability, lineage, metadata management, and data quality tooling
Familiarity with entity resolution algorithms, record deduplication, and master data management practices
Strong communication and collaboration skills, with the ability to work effectively within a cross-functional team
Working proficiency in English (B2)
Your Responsibilities:
Design, build, and maintain Databricks Lakehouse components using Delta Lake, Unity Catalog, and orchestrated Databricks Workflows
Develop and optimize both batch and event-driven data pipelines across the AWS ecosystem (S3, AWS Glue, Athena, AWS Lambda, and streaming services)
Perform robust SQL development and data modelling (including PostgreSQL / Amazon RDS), along with semantic lakehouse modelling for business entities and metrics powering knowledge graphs
Implement and oversee automated data quality frameworks, data lineage tracking, and governance standards across the platform
Lead master data management (MDM) initiatives and entity resolution pipelines to consolidate core entities (such as patients, healthcare professionals/HCPs, and healthcare accounts)
Will Be a Plus:
Familiarity with healthcare standards and terminologies (FHIR, HL7, OMOP, RxNorm, SNOMED)
Experience in Pharma, Life Sciences, or HealthTech domains