Principal Data Engineer

Company Overview

Not specified.

Job Summary

The Principal Solutions Architect will support the Drug Innovation Platform by designing, building, and maintaining high-quality data integration solutions that enable seamless data flow across the platform. This role focuses on ensuring the availability, quality, and reliability of data, which is critical for accelerating drug discovery and development. The Architect will work closely with data scientists, data engineers, and application developers to design and implement scalable data pipelines, integrate diverse data sources, and optimize data workflows. This role plays a crucial part in the delivery of high-impact data products and solutions that drive innovation and support data-driven decision-making.

Responsibilities

• Design and implement scalable data integration solutions to ensure seamless data flow across the Drug Innovation Platform.
• Collaborate with data scientists, data engineers, and application developers to optimize data workflows and enhance data quality.
• Build and manage data pipelines, ensuring the availability and reliability of data for drug discovery and development.
• Integrate diverse data sources and transform large datasets to meet project requirements.
• Apply data governance and quality management practices to maintain high standards of data integrity.
• Utilize modern data integration tools and cloud data platforms to enhance data processing capabilities.

Qualifications

• Educational Background: Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field; a Master’s degree is a plus.
• Experience: 3+ years of experience in data engineering, data integration, or software development, with hands-on experience in building and managing data pipelines.
• Technical Skills:
  • Proficiency in data processing frameworks (e.g., Apache Spark, Databricks, Kafka) and scripting languages (e.g., Python, SQL, Scala).
  • Experience with cloud data platforms (e.g., AWS, Azure, GCP) and modern data integration tools (e.g., Apache NiFi, Informatica, Talend).
  • Familiarity with data integration and ETL/ELT tools, including cloud-native services like AWS Glue, Azure Data Factory, or Google Dataflow.
  • Knowledge of data warehousing principles and data storage solutions (e.g., Snowflake, Redshift, BigQuery).
  • Experience with DevOps practices and Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
  • Understanding of data governance, data quality, and metadata management practices.
• Certifications: AWS Certified Data Engineer – Associate (or similar).

Preferred Skills

• None specified.

Experience

Minimum of 3 years of relevant experience in data engineering, data integration, or software development.

Environment

• Work Type: Full time
• Work Mode: Hybrid
• Location: Bangalore

Salary

Not specified.

Growth Opportunities

Not specified.

Benefits

Not specified.