Data Science Engineer

Job Description: -Proficiency in AWS services such as Glue, S3, SageMaker, and Snowflake Data Lake with 5-6 years of experience. -Strong programming skills in Python for data manipulation, analysis, and modeling. -Experience with distributed computing frameworks like Spark for big data processing. -Knowledge of machine learning concepts, algorithms, and tools for regression, classification, clustering, and recommendation systems. -Certifications in AWS, Python, Spark, or related technologies. Responsibilities:                                                                       -Develop and maintain ETL pipelines using AWS Glue for data ingestion, transformation, and integration from various sources. -Utilize Python and Spark for data preprocessing, feature engineering, and model development. -Design and implement data lake architecture using Snowflake Data Lake, Snowflake data warehouse and S3 for scalable and efficient storage and processing of structured and unstructured data. -Leverage SageMaker for model training, evaluation, deployment, and monitoring in production environments. -Collaborate with data scientists, analysts, and business stakeholders to understand requirements, develop predictive models, and generate actionable insights. -Conduct exploratory data analysis (EDA) and data visualization to communicate findings and trends effectively. -Stay updated with advancements in machine learning algorithms, techniques, and best practices to enhance model performance and accuracy. -Ensure data quality, integrity, and security throughout the data lifecycle by implementing robust data governance and compliance measures. Qualifications: -Bachelor's degree or higher in Computer Science, Data Science, Statistics, or related field. -Proficiency in AWS services such as Glue, S3, SageMaker, and Snowflake Data Lake with 5-6 years of experience. -Strong programming skills in Python for data manipulation, analysis, and modeling. -Experience with distributed computing frameworks like Spark for big data processing. -Knowledge of machine learning concepts, algorithms, and tools for regression, classification, clustering, and recommendation systems. -Familiarity with data visualization tools with Tableau for creating meaningful visualizations. -Excellent problem-solving, analytical thinking, and communication skills. -Ability to work collaboratively in a team environment and manage multiple priorities effectively. -Experience deploying machine-learning models in production environments and monitoring their performance. -Knowledge of MLOps practices, model versioning, and automated model deployment pipelines. -Familiarity with SQL, NoSQL databases, and data warehousing concepts. -Strong understanding of cloud computing principles and architectures. -Certifications in AWS, Python, Spark, or related technologies