- s a Senior Data Engineering & Platform Architect with experience in a Life Sciences/Healthcare, understands the client requirements and provides data architecture solutions.
- Provide large scale enterprise data architecture solutions expertise primarily in AWS. MS Azure or Google cloud data architecture expertise will be an added plus.
- Understands and considers all pertinent options in terms of data architecture in the areas of data extraction from client internal and external business systems, and ingestion in AWS cloud, engineering data pipelines, data hubs, data warehousing, and data lakes.
- Reviews proposals, develops PoCs, and provides effort estimates as per project needs.
- Provide oversight to data architecture solution implementation, with ability to guide a team of data engineers on projects.
- Build and standardize data architecture solution with frameworks, utilities, templates, and other demonstrable assets based on industry demand and client opportunities.
- Foster a culture of engagement and growth in data architecture and LS domain practice thru continuous learning, sharing ideas, adopting data architecture process improvements, and industry trends and best practices.
- Skill Profile
- t least 7 years of experience as a Data Architect in a large Pharmaceutical or Biotechnology company, preferably in the Commercial, Supply Chain, Manufacturing, or R&D area.
- Must have executed at least 2 large programs based on data architecture, leading data architecture teams to construct an integrated enterprise level solution. Experience working on Data Analytics project will be an added plus.
- Excellent understanding and experience of data architecture concepts, approaches, strategies, implementation methodologies, migration, RESTful framework, micros services, and Service Bus.
- Solid experience with AWS components and concepts like S3, Redshift, Glue, Data Lakes, IAM, EC2, EBS/EFS, ELB/ALB, AutoScaling, RDS and replication techniques, VPC, Subnets, Elastic IP, Route53, CloudWatch, CloudFront, Lambda, Databricks, PySpark, and CloudFormation.
- Integration of Identity and Access Management with the APIs in the consumption layer utilizing OAUTH/SAML protocols.
- Experience with big data technologies like Hadoop, Kafka, Hive, and Presto is preferred.
- Strong background in Data warehousing and data modeling, designing and architecting data hubs, data lakes, and data marts. Design and architecture considerations for real-time vs batch data orchestration.
- Proficiency with multiple RDBMS like SQL Server, Oracle, and NoSql databases such as MongoDB, Cassandra, or HBase.
- Customer engagement with strong communication, presentation, and articulation skills.
- Team player with ability to work in a dynamic environment.
- Required domain expertise/capabilities
- Domain knowledge and experience working in a pharmaceutical or biotechnology company, preferably Commercial, Supply Chain, or Manufacturing, or R&D is required.
- Understanding of domain specific business processes, systems, and data.
- Educational Background
- BTech/BE/B Sc (Computer Sciences) or Master's in Computer Applications
- Years of experience required for position -
- Location for the position - USA
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Description
Job Description (Please provide summary of the position):Provide Data Engineering & platform architecture solutions/support in line with the identified needs and expectations of TCS's NA LS clients and NA LS Data & Analytics practice.
Responsibilities:
Qualifications:
(Please list all required qualifications - Refer Subheads a, b, c and d)