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Engineering Data Analyst Data Engineer Engineering Data Leadership
As a Data Engineer at GFT, you will be responsible for managing, designing, and enhancing data systems and workflows that drive key business decisions. The role is focused 75% on data engineering, involving the construction and optimization of data pipelines and architectures, and 25% on supporting data science initiatives through collaboration with data science teams for machine learning workflows and advanced analytics. You will leverage technologies like Python, Airflow, Kubernetes, and AWS to deliver high-quality data solutions. Key Activities - Architect, develop, and maintain scalable data infrastructure, including data lakes, pipelines, and metadata repositories, ensuring the timely and accurate delivery of data to stakeholders. - Work closely with data scientists to build and support data models, integrate data sources, and support machine learning workflows and experimentation environments. - Develop and optimize large-scale, batch, and real-time data processing systems to enhance operational efficiency and meet business objectives. - Leverage Python, Apache Airflow, and AWS services to automate data workflows and processes, ensuring efficient scheduling and monitoring. - Utilize AWS services such as S3, Glue, EC2, and Lambda to manage data storage and compute resources, ensuring high performance, scalability, and cost-efficiency. - Implement robust testing and validation procedures to ensure the reliability, accuracy, and security of data processing workflows. - Stay informed of industry best practices and emerging technologies in both data engineering and data science to propose optimizations and innovative solutions.
- Bachelor's in Software Engineering or related fields - 12+ years of experience in total - 5+ years as a Data Engineer, hands on Python programming ]- Core Expertise: Proficiency in Python for data processing and scripting (pandas, pyspark), workflow automation (Apache Airflow), and experience with AWS services (Glue, S3, EC2, Lambda). - Containerization & Orchestration: Experience working with Kubernetes and Docker for managing containerized environments in the cloud. - Data Engineering Tools: Hands-on experience with columnar and big data databases (Athena, Redshift, Vertica, Hive/Hadoop), along with version control systems like Git. - Cloud Services: Strong familiarity with AWS services for cloud-based data processing and management. - CI/CD Pipeline: Experience with CI/CD tools such as Jenkins, CircleCI, or AWS CodePipeline for continuous integration and deployment. - Data Engineering Focus (75%): Expertise in building and managing robust data architectures and pipelines for large-scale data operations. - Data Science Support (25%): Ability to support data science workflows, including collaboration on data preparation, feature engineering, and enabling experimentation environments.
- Competitive Compensation - Benefits package including comprehensive medical, dental, vision and others - Company Culture based on our Core Values - Professional Development Training with Individual Development Plans to map out your career growth - Opportunity to work in a global environment with diverse teams built with colleagues from around the world - Opportunity to work with technology industry leaders in the financial services industry - Opportunity to work for big name clients in capital markets, banking and other industries
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Open cho uv 9 years total ko bạn?
Candidate must have 12+ years in total
Hi role Lead này, vẫn yêu cầu total 12+ yoe như role SA đúng k team ha?
Yes that's correct