Data Engineer
2 weeks ago
About the Role:
We are currently seeking a mid-level Data Engineer to join our team to develop and maintain scalable data pipelines to support growing data volume and complexity. This position involves close interaction with cross-functional teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
Responsibilities:
Data Pipeline Development and Maintenance:
• Design, build, and maintain data pipelines and ETL processes on AWS to support analytics and machine learning initiatives.
• Use AWS services such as RDS, Glue, Lambda, S3 to manage and process large data sets.
Machine Learning infrastructure:
• Enable model training, testing, and deployment using SageMaker and other AWS ML services.
• Design and build scalable infrastructure for deploying machine learning models into production, incorporating best practices for monitoring, logging, and retraining models.
• Implement and automate workflows that support the end-to-end ML lifecycle, including data preprocessing, feature engineering, and model evaluation.
DevOps and Automation
• Incorporate DevOps best practices into data engineering workflows, focusing on automation, CI/CD, and infrastructure as code (IaC) for repeatable, scalable solutions.
• Develop and maintain IaC templates (e.g. Terraform, CloudFormation) to provision and manage AWS resources for data engineering and ML tasks.
• Build monitoring, logging, and alerting systems to ensure data pipeline and model uptime,
performance, and data quality.
Qualifications:
• You'll typically have a degree in a computer science, mathematical or science-based subject.
Knowledge, Skills and Abilities Required:
• Must hold hands-on experience with ETL process.
• Cloud Expertise: Strong experience with AWS, including services like S3, Glue, Lambda, and SageMaker.
• Programming: Advanced proficiency in Python, including experience with data processing libraries (e.g. Pandas) and automation.
• Machine Learning: Familiarity with machine learning pipelines, especially using SageMaker for model training, deployment, and monitoring.
• DevOps: Experience with DevOps practices, including CI/CD pipelines, Infrastructure as Code (Terraform, CloudFormation), and monitoring (CloudWatch).
• Data Engineering: Solid understanding of data warehousing, ETL/ELT processes.
• Collaboration: Strong communication skills and experience working in cross-functional Agile teams.
• Excellent analytical and problem-solving skills.
• Effective listening skills to understand the requirements of the business.
• Planning, time management and organizational skills.
• The ability to deliver under pressure and to tight deadlines.
About Eastvantage:
At Eastvantage, our mission is to create meaningful jobs and provide careers that are knowledge-based, inspiring, and always with the potential for development and growth.
We are an independently owned Global business solutions company enabling offshore operations from our locations in the Philippines, India, Bulgaria, Vietnam, Morocco and Belgium. With European roots, we provide our services to global companies that have offices in every populated continent in the world. We have been in the industry for over a decade, growing from a handful to over 1200 happy employees over the years.
We invite you to navigate through our website to get to know who we are, to see what sets us apart in culture and thinking. Join us and be part of our success story
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