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AWS Data Engineer
3 weeks ago
Collaborate with clients to understand their business requirements and design scalable and efficient data architectures on the AWS platform.
Develop and implement data pipelines using AWS services such as AWS Glue, AWS Redshift, and Amazon S3.
Design and implement Extract, Transform, Load (ETL) processes to integrate data from diverse sources into AWS.
Ensure data consistency, accuracy, and reliability across integrated datasets.
Optimize data processing workflows for performance and cost efficiency.
Conduct performance tuning and troubleshooting of data pipelines.
Implement and enforce data security best practices and ensure compliance with relevant data protection regulations and industry standards.
Work closely with clients and internal teams to understand and address their data engineering needs.
Communicate technical solutions effectively to non-technical stakeholders.
Document data engineering processes, architectures, and best practices.
Contribute to the development of internal knowledge repositories.
Qualifications :
Bachelor's degree in Computer Science, Information Technology, or a related field.
3-10 years of professional experience as a data engineer, with a focus on Amazon Web Services (AWS).
Strong proficiency in AWS services such as AWS Glue, AWS Redshift, Amazon S3, and others.
Experience with SQL and NoSQL databases.
Strong programming skills in languages such as Python, Java
Knowledge of data modeling, ETL processes, and data warehousing concepts.
Familiarity with data security and compliance requirements.
Excellent problem-solving and communication skills.
Proven ability to work in a collaborative team environment
AWS Certified Big Data - Specialty or AWS Certified Data Analytics - Specialty certification.
Previous consulting experience or experience working in client-facing roles.
Primary mandatory skills :
Strong proficiency in AWS services such as AWS Glue, AWS Redshift, Amazon S3, and others.
Experience with SQL and NoSQL databases.
of AWS SageMaker, Cloud-based platforms for building, training, and deploying machine learning models.
in SQL with the ability to write complex queries and stored procedures.
Secondary Skills:
with machine learning and AI-related data engineering tasks.
Expertise in BFSI, Fintech, Life science, Manufacturing, Telecom, Media & Entertainment
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