AWS Data Engineer (100% Remote) (Life Sciences)

Educational Qualification*

BE / MCA / Any Master degree in Computer Science

Job Description of Role* (RNR)
(Mandatory - Minimum 500 words)

Job Overview:
We are seeking a highly experienced Senior AWS Data Engineer Lead to join our team. The ideal candidate will have extensive experience with AWS data services and a strong background in data engineering. You will be responsible for designing, building, and maintaining scalable data pipelines, ensuring the efficient processing and storage of large datasets, and leading data engineering projects. Key Responsibilities:
Data Pipeline Development: Design, develop, and maintain scalable data pipelines using AWS services such as MWAA, Glue, Redshift, S3, and Lambda.
ETL Processes: Implement and manage ETL (Extract, Transform, Load) processes to ensure data is accurately and efficiently processed and stored.
Data Integration: Integrate data from various sources, ensuring data quality and consistency.
Data Modeling: Develop and maintain data models to support analytics and reporting needs.
Performance Optimization: Optimize data processing and storage solutions for performance and cost-efficiency.
Project Leadership: Lead data engineering projects, providing technical direction and mentorship to junior engineers.
Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
Monitoring and Troubleshooting: Monitor data pipelines and troubleshoot issues to ensure reliable data flow.
Documentation: Maintain comprehensive documentation of data pipelines, processes, and architectures.

Primary (Must have skills)*

Experience: Minimum of 10 years of experience in data engineering with a focus on AWS data services.
Skills: Proficiency in AWS services (Glue, Redshift, S3, Lambda, MWAA, etc.), SQL, Python, and ETL tools. Proficiency in virtualizations like the EC2, EKS, ECS, ECR, Fargate Certifications: AWS Certified Data Analytics Specialty or AWS Certified Solutions Architect preferred.
Communication: Excellent communication skills, with the ability to work collaboratively in a team environment.
Life Science Pharma & Commercial Operations Domain Knowledge is must

Secondary Skills (Good To have)*

Advanced Skills: Experience with big data technologies such as Hadoop, Spark, or Kafka.
Problem-Solving: Strong analytical and problem-solving skills.
Adaptability: Ability to adapt to new technologies and methodologies quickly.
Leadership: Proven experience in leading data engineering projects and mentoring junior

Soft skills/other skills (If any)

- Negotiation skills
- Willingness to learn new technologies as per project need
- Time management
- Ready to take ownership