Data Engineer

Company/Client Name:Indegene

Experience: 5+

Location

Mode of Hiring :

Mode of Work : Onsite

Job Summary:

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.