Data Engineer

Key Responsibilities:

• Develop, optimize, and maintain

  ETL/ELT pipelines

  using

  Dataiku

  and SQL-based transformations.
• Work with

  clinical, research, and commercial datasets

  (e.g., patient data, clinical trials, drug safety, sales, etc.).
• Integrate data from multiple sources such as

  ERP, CRM, laboratory systems

  , and

  external data providers

  .
• Build and manage

  data workflows, recipes, and visual pipelines

  in Dataiku.
• Ensure

  data quality, lineage, and compliance

  with pharma regulations (GxP, HIPAA, GDPR, etc.).
• Collaborate with

  data scientists

  to operationalize predictive models and AI/ML workflows within Dataiku.
• Design and maintain

  data models, schemas, and queries

  to support analytics and reporting.
• Optimize SQL queries and database performance for large-scale data processing.
• Document processes, pipelines, and data dictionaries for reproducibility and audit readiness.

Required Skills & Qualifications:

• Strong hands-on experience in Dataiku DSS (Data Science Studio)

  building flows, recipes, scenarios, and automation.

• Advanced SQL skills

  for data transformation, optimization, and troubleshooting.
• Solid understanding of

  data warehousing concepts

  ,

  ETL processes

  , and

  data integration techniques

  .
• Experience with

  pharma/life sciences data

  — familiarity with data models such as

  CDISC, HL7, LOINC, MedDRA, or SDTM

  preferred.
• Proficiency with

  relational databases

  (e.g., Snowflake, Oracle, PostgreSQL, SQL Server).
• Experience with

  Python

  or

  Spark

  for data manipulation (nice to have).
• Knowledge of

  data governance, quality frameworks, and regulatory compliance

  in pharma environments.
• Strong analytical, problem-solving, and communication skills.