AWS Data Engineer

Position - AWS Data Engineer

Experience Range: 7 to 11 Years

Location: Remote

Shift Timings: 12 PM to 9 PM

Primary Skills: Python, Pyspark, SQL, AWS

Responsibilities

· Data Architecture: Develop and maintain the overall data architecture, ensuring scalability, performance, and data quality.

· AWS Data Services: Expertise in using AWS data services such as AWS Glue, S3, SNS, SES, Dynamo DB, Redshift, Cloud formation, Cloud watch, IAM, DMS, Event bridge scheduler etc.

· Data Warehousing: Design and implement data warehouses on AWS, leveraging AWS Redshift or other suitable options.

· Data Lakes: Build and manage data lakes on AWS using AWS S3 and other relevant services.

· Data Pipelines: Design and develop efficient data pipelines to extract, transform, and load data from various sources.

· Data Quality: Implement data quality frameworks and best practices to ensure data accuracy, completeness, and consistency.

· Cloud Optimization: Optimize data engineering solutions for performance, cost-efficiency, and scalability on the AWS cloud.

· Team Leadership: Mentor and guide data engineers, ensuring they adhere to best practices and meet project deadlines.

Qualifications

· Bachelor’s degree in computer science, Engineering, or a related field.

· 6-7 years of experience in data engineering roles, with a focus on AWS cloud platforms.

· Strong understanding of data warehousing and data lake concepts.

· Proficiency in SQL and at least one programming language (Python/Pyspark).

· Good to have - Experience with any big data technologies like Hadoop, Spark, and Kafka.

· Knowledge of data modeling and data quality best practices.

· Excellent problem-solving, analytical, and communication skills.

· Ability to work independently and as part of a team.

· Preferred Qualifications

· Certifications in AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect - Data.