Data Engineer

We are seeking a skilled and experienced Data Engineer with a minimum of 5 years of expertise in data engineering and data migration projects. The ideal candidate will have a strong proficiency in SQL, Python, data modeling, data warehousing, and ETL pipeline development. It is essential to have hands-on experience with big data tools such as Hadoop and Spark, as well as familiarity with various AWS services including Redshift, S3, Glue, EMR, and Lambda. This position offers a fantastic opportunity to contribute to large-scale data solutions that drive data-informed decision-making and operational efficiency. As a Data Engineer, your responsibilities will include designing, building, and maintaining scalable data pipelines and ETL processes. You will be tasked with developing and optimizing data models and data warehouse architectures, as well as implementing and managing big data technologies and cloud-based data solutions. Your role will involve performing data migration, transformation, and integration from multiple sources, collaborating with cross-functional teams to understand data requirements, and ensuring data quality, consistency, and security throughout all data pipelines and storage systems. Additionally, you will be responsible for optimizing performance and managing cost-efficient AWS cloud resources. Basic qualifications for this role include a Master's degree in Computer Science, Engineering, Analytics, Mathematics, Statistics, IT, or a related field, along with a minimum of 5 years of hands-on experience in Data Engineering and data migration projects. Proficiency in SQL and Python for data processing and analysis is required, as well as a strong background in data modeling, data warehousing, and building data pipelines. The ideal candidate will have practical experience with big data technologies like Hadoop and Spark, and expertise in utilizing AWS services such as Redshift, S3, Glue, EMR, Kinesis, Firehose, Lambda, and IAM. An understanding of ETL development best practices and principles is also expected. Preferred qualifications include knowledge of data security and data privacy best practices, experience with DevOps and CI/CD practices related to data workflows, familiarity with data lake architectures and real-time data streaming, strong problem-solving abilities, attention to detail, excellent verbal and written communication skills, and the ability to work both independently and collaboratively in a team environment. Desirable skills for this role include experience with orchestration tools like Airflow or Step Functions, exposure to BI/Visualization tools like QuickSight, Tableau, or Power BI, and an understanding of data governance and compliance standards.,