Role Data Architect
Location India, Remote (Work from Anywhere in India)
Minimum Qualification B. Tech. (or equivalent) from an accredited institution
Indicative Experience 8+ Years
Domain Preferably Life-Sciences/Pharma.
Other benefits Health Insurance, Provident Fund, Reimbursement of Certification Expenses, Gratuity, 24x7 Health Desk
About Norstella
At Norstella, our mission is simple: to help our clients bring life-saving therapies to market quicker—and help patients in need.
Founded in 2022, but with history going back to 1939, Norstella unites best-in-class brands to help clients navigate the complexities at each step of the drug development life cycle —and get the right treatments to the right patients at the right time.
Each organization (Citeline, Evaluate, MMIT, Panalgo, The Dedham Group) delivers must-have answers for critical strategic and commercial decision-making. Together, via our market-leading brands, we help our clients:
· Citeline – accelerate the drug development cycle
· Evaluate – bring the right drugs to market
· MMIT – identify barrier to patient access
· Panalgo – turn data into insight faster
· The Dedham Group – think strategically for specialty therapeutics
By combining the efforts of each organization under Norstella, we can offer an even wider breadth of expertise, cutting-edge data solutions and expert advisory services alongside advanced technologies such as real-world data, machine learning and predictive analytics.
As one of the largest global pharma intelligence solution providers, Norstella has a footprint across the globe with teams of experts delivering world class solutions in the USA, UK, The Netherlands, Japan, China and India.
Have you wondered how life saving drugs and therapies are created, tested, marketed and made available to patients in need? Have you wondered how clinical trials are conducted at a global scale? How governments and health authorities regulate various organizations participating in this marketplace? Have you wondered how those companies and insurance providers price a certain drug, and how a care provider determines the right treatment for a given patient? If yes, Norstella could the next step in your career.
Reporting into Technology Manager, Senior Software Engg will work with internal and external developers responsible for the development and subsequent support of the various platform services components underpinning all the customer facing applications across Norstella. As part of a large technology group, the Senior Software Engg will work with product management, architecture and other software engineering teams in support of the product development roadmap.
We are looking for an experienced senior software engineer with great communication skills, deep experience in software engineering, and most importantly, the ability and willingness to keep learning in this ever-changing technology landscape.
Overview: We are seeking an experienced Data Architect to join our team and take charge of designing and managing our data infrastructure. The ideal candidate will have extensive experience with Snowflake, Redshift, PostgreSQL, data pipelines, ETL processes, AWS, and large datasets. Experience with life science data is highly desirable. This role requires collaboration with the Data Science team and a strong ability to deliver high-quality data solutions, including performance tuning and data model design.
Key Responsibilities:
- Data Architecture Design:
- Design and implement scalable, high-performance data models and data architectures to meet business requirements.
- Develop and maintain data models for both structured and unstructured data, ensuring optimal performance and reliability.
- Data Pipeline Development:
- Build and manage data pipelines for efficient data ingestion, processing, and integration.
- Implement ETL processes to transform and load data from various sources into Snowflake, Redshift, PostgreSQL, and other data platforms.
- Cloud Services Management:
- Utilize AWS services (such as S3, Redshift, Glue, and Lambda) for data storage, processing, and analytics.
- Ensure data infrastructure is scalable, cost-effective, and aligns with industry best practices.
- Collaboration with Data Science Team:
- Work closely with Data Scientists to understand their data needs and ensure data availability and quality for analysis and modeling.
- Provide data support and troubleshooting for data science projects.
- Large Data Set Management:
- Handle very large data sets with a focus on performance optimization and efficient querying.
- Implement strategies for data partitioning, indexing, and caching to enhance performance.
- Performance Tuning:
- Monitor and optimize data systems for performance, including query optimization and resource management.
- Identify and resolve bottlenecks in data processing and retrieval.
- Data Delivery Ownership:
- Take ownership of data delivery processes, ensuring data is accurate, timely, and accessible.
- Establish and maintain data governance policies and procedures.
- Life Science Data Expertise:
- Apply knowledge of life science data and industry-specific requirements to inform data architecture and modeling decisions.
- Ensure compliance with relevant regulations and standards for handling life science data.
Required Skills:
- Snowflake: Proficiency in designing, implementing, and managing Snowflake environments and solutions.
- Redshift: Expertise in Amazon Redshift for data warehousing and analytics.
- PostgreSQL: Advanced knowledge of PostgreSQL for relational database management.
- ETL Processes: Extensive experience with ETL tools and frameworks, including data extraction, transformation, and loading.
- AWS: Strong knowledge of AWS data services (e.g., S3, Redshift, Glue, Lambda) and cloud architecture best practices.
- Data Modeling: Expertise in designing data models and schemas for both transactional and analytical use cases.
- Large Data Sets: Ability to manage and optimize large volumes of data efficiently.
- Performance Tuning: Skills in tuning database queries and optimizing data processing workflows.
- Collaboration: Experience working with data science teams to support analytics and machine learning initiatives.
- Data Delivery: Proven track record of owning and managing data delivery processes to ensure high data quality and availability.
- Life Science Data Knowledge: Familiarity with life science data types, regulatory considerations, and industry-specific standards.
