002AVM - Data Engineer (Remote)

• Duration of Contract – 4 months with possible extension
• Start Date: ASAP
• Experience Level: 10+ Years

Job Description:

We are seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team. The ideal candidate should have a robust background in the various phases of ETL data applications, including data ingestion, preprocessing, and transformation. This role is perfect for someone who thrives in a fast-paced environment and is passionate about leveraging data to drive business success.

Key Responsibilities:

• Design and implement efficient data ingestion pipelines to collect and process large volumes of data from various sources.
• Hands-on experience with AWS Database Migration Service for seamless data migration between databases.
• Develop and maintain scalable data processing systems, ensuring high performance and reliability.
• Utilize advanced data transformation techniques to prepare and enrich data for analytical purposes.
• Collaborate with cross-functional teams to understand data needs and deliver solutions that meet business requirements.
• Manage and optimize cloud-based infrastructure, particularly within the AWS ecosystem, including services such as S3, Step-Function, EC2, and IAM.
• Experience with cloud platforms and understanding of cloud architecture.
• Knowledge of SQL and NoSQL databases, data modelling, and data warehousing principles.
• Familiarity with programming languages such as Python or Java.
• Implement security and compliance measures to safeguard data integrity and privacy.
• Monitor and tune the performance of data processing systems to ensure optimal efficiency.
• Stay updated with emerging trends and technologies in data engineering and propose adaptations to existing systems as needed.
• Proficient in AWS Glue for ETL (Extract, Transform, Load) processes and data cataloging.
• Hands-on experience with AWS Lambda for serverless computing in data workflows.
• Knowledge of AWS Glue Crawler Kinesis RDS for batch / real-time data streaming
• Familiarity with AWS Redshift for large-scale data warehousing and analytics.
• Skillful in implementing data lakes using AWS Lake Formation for efficient storage and retrieval of diverse datasets.
• Experience with AWS Data Pipeline for orchestrating and automating data workflows.
• In-depth understanding of AWS CloudFormation for infrastructure as code (IaC) deployment.
• Proficient in AWS CloudWatch for monitoring and logging data processing workflows.
• Familiarity with AWS Glue DataBrew for visual data preparation and cleaning.
• Expertise in optimizing data storage costs through AWS Glacier and other cost-effective storage solutions.
• Hands-on experience with AWS DMS (Database Migration Service) for seamless data migration between different databases.
• Knowledge of AWS Athena for interactive query processing on data stored in Amazon S3.
• Experience with AWS AppSync for building scalable and secure GraphQL APIs.

Qualifications:

• A minimum of 10 years of experience in data engineering or a related field.
• Strong background in big data application phases, including data ingestion, preprocessing, and transformation.

Education:

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field. A Master’s degree is preferred.

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