Data Engineer AWS | Python, SQL, Redshift & Data Lake
Indexed description
Required Qualifications
- Strong experience in Data Engineering within AWS environments.
- Hands-on experience with Amazon S3, Amazon Redshift, AWS Lambda, and AWS Step Functions.
- Proven expertise in designing, developing, and maintaining scalable ETL/ELT data pipelines.
- Strong proficiency in Python for data processing, automation, and application development.
- Advanced SQL skills and solid understanding of Data Warehouse concepts.
- Experience integrating data from REST APIs and JSON-based services.
- Strong knowledge of data modeling and analytical schema design.
- Experience working with Medallion Architecture (Bronze, Silver, and Gold layers).
- Advanced English communication skills, with the ability to collaborate effectively in a global environment.
- Ability to work independently and interact directly with clients and cross-functional teams.
- Experience with AWS Glue, Amazon Athena, and Amazon EMR.
- Knowledge of data quality, monitoring, and observability tools.
- Experience with event-driven architectures.
- Hands-on experience with streaming data pipelines using Kafka or Amazon Kinesis.
- Knowledge of CI/CD practices for data workflows and data platforms.
- Experience with Infrastructure as Code (Terraform or AWS CloudFormation).
- Experience delivering enterprise Analytics and Data Lake solutions.
- Design, develop, and optimize data pipelines within AWS environments.
- Build and maintain data ingestion processes from APIs and various internal and external data sources.
- Transform, process, and deliver data for analytical consumption using Amazon Redshift.
- Ensure data quality, integrity, availability, and governance across the entire data lifecycle.
- Develop monitoring, alerting, and error-handling mechanisms for data pipelines.
- Optimize storage, query performance, and processing efficiency across Data Lake and Data Warehouse platforms.
- Collaborate closely with Data Analysts, Data Scientists, Architects, and business stakeholders.
- Create and maintain technical documentation for data models, integrations, and pipeline processes.
- Lead technical discussions with clients and global teams, ensuring successful delivery of data solutions.
- Full-time, permanent position (CLT).
- Flexible working hours.
- Transportation allowance.
- Meal voucher.
- Childcare assistance.
- Life insurance.
- Funeral assistance.
- Medical insurance.
- Dental insurance.
- Exposure to both national and international projects.
- Opportunity to work with global clients and multicultural teams.
- Potential for international career mobility within Infosys.
- Advanced English proficiency for collaboration with international stakeholders and global teams.
EEO
Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.
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