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.
Qualifications
Bachelors 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
AWS data developers with 6-10 years experience certified candidates (AWS data engineer associate or AWS solution architect) are preferred
Skills required - SQL, AWS Glue, PySpark, Air Flow, CDK, Red shift
Good communication skills and can deliver independently
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data EngineerEmployement Type: Full time