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Job Description:

The Future Begins Here:

At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet.

Bengaluru, the city, which is India's epicenter of Innovation, has been selected to be home to Takeda's recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement.

At Takeda's ICC we Unite in Diversity:

Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team

About the Role:

As a Senior Database Developer within the PlasmaDerived Therapies (PDT) Technology ecosystem, you will serve as a subject matter expert and hands-on technical lead for the design, development, and optimization of enterprise-grade database solutions. With deep expertise in SQL Server, Amazon RDS, and EC2-hosted database environments, you will drive the architecture and delivery of robust, scalable, and compliant data platforms that power critical life sciences operations including clinical data management, regulatory submissions, pharmacovigilance, and commercial analytics.

You will combine advanced database engineering skills, life sciences domain knowledge, and modern cloud-native data stack expertise to ensure data systems are performant, reliable, secure, and audit-ready. You will collaborate across data engineering, analytics, and platform teams to align data solutions with regulatory requirements (GxP, 21 CFR Part 11, HIPAA) and enterprise architecture standards.

How You Will Contribute

Database Design & Development

• Design, develop, and maintain high-performance relational databases using SQL Server (2016–2022)
• Architect and implement database schemas, stored procedures, functions, triggers, views, and indexing strategies for complex life sciences data workloads.
• Work closely with Integration teams, providing ETL ready data for loading clinical trials. Lab systems and disparate source systems.
• Create and maintain data models (logical and physical) aligned with life sciences data standards including CDISC, CDASH, and SDTM.
• Implement data partitioning, archiving, and purging strategies to manage large-scale datasets efficiently.
  
  

Cloud Database Engineering – AWS RDS & EC2

• Design, deploy, and administer databases on Amazon RDS (SQL Server, PostgreSQL, MySQL)
• Manage database instances on Amazon EC2.
• Understanding of leveraging Databricks as Lakehouse to maintain the ODS system acting as central connection point to multiple applications.
• Implement Multi-AZ deployments, read replicas, automated backups, and point-in-time recovery configurations on AWS RDS.
• Optimize database performance on cloud infrastructure through parameter group tuning, storage optimization, and right-sizing of EC2 / RDS instances.
• Leverage AWS native services such as AWS Secrets Manager, IAM roles, VPC configurations, and Security Groups to enforce database security best practices.
• Support database migration initiatives from on-premises SQL Server environments to AWS using AWS DMS and Schema Conversion Tool (SCT).
  
  

Performance Tuning & Query Optimization

• Conduct systematic performance analysis using SQL Server Profiler, Execution Plans, Dynamic Management Views (DMVs), and AWS RDS Performance Insights.
• Identify and resolve query bottlenecks, index fragmentation, blocking, and deadlock issues to ensure SLA compliance for critical life sciences applications.
• Define and enforce indexing standards, statistics management policies, and query optimization guidelines across development teams.
• Proactively monitor and tune database workloads to support high-availability requirements for regulated applications.
  
  

Data Governance, Compliance & Security

• Ensure all database designs and operations adhere to GxP, 21 CFR Part 11, HIPAA, and GDPR compliance requirements applicable to life sciences data.
• Implement robust role-based access control (RBAC), column-level encryption, Transparent Data Encryption (TDE), and auditing mechanisms.
• Maintain audit trails, change management logs, and data lineage documentation required for regulatory submissions and inspections.
• Partner with data governance teams to establish and enforce data quality rules, master data definitions, and metadata standards across clinical and commercial datasets.
• Support CSV (Computer System Validation) activities for regulated database systems including authoring IQ/OQ/PQ protocols and supporting validation testing.
  
  

AWS Cloud Integration & Modern Data Stack

• Leverage core AWS services including EC2, RDS, S3, Lambda, Glue, and Redshift
• Integrate database solutions with cloud-native data pipelines utilizing AWS for ETL orchestration and S3 as a data lake landing zone.
• Support implementation of data warehousing solutions on Amazon Redshift for analytics and reporting use cases across life sciences functions.
• Apply AWS best practices for cost optimization, performance efficiency, and reliability within database infrastructure.
• Participate in cloud infrastructure provisioning using IaC principles (CloudFormation, Terraform) for repeatable, auditable database environment deployments.
  
  

Collaboration, Documentation & Technical Leadership

• Serve as the database technical authority within cross-functional squads comprising data engineers, software developers, QA engineers, and business analysts.
• Conduct database design reviews, code reviews, and technical walkthroughs to maintain engineering quality and standards.
• Produce and maintain high-quality technical documentation including data dictionaries, ERDs, deployment runbooks, and DR procedures.
• Mentor junior database developers and data engineers, fostering growth in database engineering practices and life sciences data domain knowledge.
• Partner with DevOps and platform teams to integrate database CI/CD practices using tools such as Flyway, Liquibase, or equivalent schema migration frameworks.
  
  

Minimum Requirements / Qualifications

• 7+ years of professional experience in database development and administration, with a strong focus on enterprise SQL Server environments.
• Deep expertise in Microsoft SQL Server (2016/2019/2022)
• Hands-on experience with Amazon RDS (SQL Server, PostgreSQL) & EC2
• Proven experience deploying and managing databases on Amazon EC2.
• Strong working knowledge of AWS core services including S3, IAM, VPC, Secrets Manager, CloudWatch, and AWS DMS.
• Demonstrated experience in the Life Sciences domain
• Proficiency in advanced T-SQL development including complex stored procedures, dynamic SQL, window functions, CTEs, and performance-critical query patterns.
• Exposure designing and implementing ETL/ELT pipelines and data integration workflows for large-scale, multi-source datasets.
• Solid understanding of data modelling, normalization, dimensional modelling, and physical database design principles.
• Understanding of Data Governance, Data lifecycle concepts in an enterprise setup.
• Familiarity with life sciences data standards such as CDISC, CDASH, SDTM, and ADaM.
• Strong analytical and problem-solving skills with the ability to diagnose and resolve complex database performance and reliability issues.
• Excellent communication skills, with the ability to convey technical database concepts to non-technical stakeholders.
  
  

Preferred Requirements

• Experience with enterprise data warehousing and analytics workloads; SQL server is must, Databricks is a plus.
• Hands-on experience with AWS Glue, AWS Lambda, and Step Functions for serverless data pipeline orchestration.
• Familiarity with Infrastructure as Code tools such as Terraform or AWS CloudFormation for database environment provisioning.
• Experience with schema migration and versioning tools such as Flyway or Liquibase integrated within CI/CD pipelines.
• Knowledge of NoSQL database technologies (DynamoDB, MongoDB) for hybrid data architecture use cases is a nice to have.
• Understanding of modern data Lakehouse patterns using Apache Spark, Delta Lake, or AWS Lake Formation.
• Experience with any of the data visualization and BI tools such as Power BI, Tableau, or QuickSight consuming database-layer data.
• Familiarity with GxP Computer System Validation (CSV) practices and authoring validation documentation.
• Experience in Agile/Scrum delivery environments with tools such as Jira and Confluence; along with code versioning tool such as GitHub.
• Certification in any Cloud Data platforms; AWS or Azure or GCP will be added advantage
  
  

BENEFITS:

It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are

• Competitive Salary + Performance Annual Bonus
• Flexible work environment, including hybrid working
• Comprehensive Healthcare Insurance Plans for self, spouse, and children
• Group Term Life Insurance and Group Accident Insurance programs
• Employee Assistance Program
• Broad Variety of learning platforms
• Diversity, Equity, and Inclusion Programs
• Reimbursements – Home Internet & Mobile Phone
• Employee Referral Program
• Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 calendar days)
  
  

ABOUT ICC IN TAKEDA:

• Takeda is leading a digital revolution. We're not just transforming our company; we're improving the lives of millions of patients who rely on our medicines every day.
• As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.
  
  

Locations:

IND - Bengaluru

Worker Type:

Employee

Worker Sub-Type:

Regular

Time Type:

Full time