Job Description:

We are seeking a talented Mid-Level Data Engineer with a minimum of 5 years of experience to join our dynamic team. The ideal candidate will have strong expertise in utilizing Amazon Web Services (AWS) tools such as Amazon Sagemaker, EMR, and Jupyter to build robust data pipelines and solutions. If you have a passion for leveraging data to drive insights and thrive in a collaborative environment, we want to hear from you.

Key Responsibilities:

Design, develop, and maintain scalable data pipelines using AWS services such as Sagemaker, EMR, Glue, and Lambda.
Collaborate with cross-functional teams to gather requirements and implement data solutions that meet business needs.
Optimize and fine-tune data pipelines for performance, reliability, and cost efficiency.
Develop and maintain Jupyter notebooks for data exploration, analysis, and visualization.
Implement data governance best practices to ensure data quality, integrity, and security.
Work closely with data scientists to deploy machine learning models into production environments.
Troubleshoot and debug data pipeline issues in a timely manner to minimize downtime.
Stay current with emerging technologies and best practices in the field of data engineering.
Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field. Advanced degree preferred.
Minimum of 5 years of experience in data engineering or a related role.
Strong proficiency in Python programming language.
Hands-on experience with AWS services such as Sagemaker, EMR, Glue, Lambda, and S3.
Experience with big data technologies such as Hadoop, Spark, or Kafka.
Familiarity with containerization technologies such as Docker and Kubernetes.
Excellent problem-solving skills and attention to detail.
Strong communication and interpersonal skills, with the ability to collaborate effectively with team members across different disciplines.
Experience working in an Agile development environment is a plus.