Job
Description
As a Data Engineer at our company, you will play a crucial role in designing, developing, and optimizing data pipelines to ensure seamless integration and transformation of data across various systems. Your expertise in Python, SQL, and AWS will be essential in building scalable and secure data solutions. Here is a breakdown of the key responsibilities, required technical skills, and professional attributes for this role: Key Responsibilities: - Design, build, and manage robust and scalable data pipelines for both batch and real-time processing. - Develop ETL processes to acquire, transform, and integrate data from multiple sources. - Build and maintain data warehouses, data lakes, and storage solutions. - Optimize data systems for performance, reliability, and scalability. - Collaborate with cross-functional teams to understand data requirements and deliver efficient solutions. - Ensure data quality, consistency, and integrity across all systems and pipelines. - Implement data governance, privacy, and security best practices. - Monitor and troubleshoot data flows and pipelines to ensure high availability and minimal downtime. - Document data architecture, workflows, and system designs for maintainability and scalability. Required Technical Skills: Must Have Skills: - Strong proficiency in Python programming and SQL. - Hands-on experience in ETL design and development using tools like AWS Glue, Apache Airflow, or Talend. - Expertise in AWS Cloud Services such as S3, Redshift, Lambda, and Glue. - Experience with Big Data frameworks like Apache Spark, Hadoop, or Kafka. - Strong understanding of data modeling, data warehousing, and data architecture principles. - Proficiency in Git version control and CI/CD automation pipelines. Good to Have Skills: - Exposure to GCP or Azure cloud platforms. - Familiarity with data orchestration tools and data governance frameworks. - Experience working with structured and unstructured data at scale. Professional Attributes: - Excellent problem-solving and analytical thinking skills. - Strong communication and collaboration skills across teams. - Proven ability to deliver end-to-end data solutions with minimal supervision. - Detail-oriented mindset with a focus on data quality and automation. About the Company: [Omitting this section as it was not provided in the Job Description] Educational Qualification: - Bachelors or Masters degree in Computer Science, Engineering, Information Systems, or a related field. - Minimum 15 years of full-time education required. As a Data Engineer at our company, you will play a crucial role in designing, developing, and optimizing data pipelines to ensure seamless integration and transformation of data across various systems. Your expertise in Python, SQL, and AWS will be essential in building scalable and secure data solutions. Here is a breakdown of the key responsibilities, required technical skills, and professional attributes for this role: Key Responsibilities: - Design, build, and manage robust and scalable data pipelines for both batch and real-time processing. - Develop ETL processes to acquire, transform, and integrate data from multiple sources. - Build and maintain data warehouses, data lakes, and storage solutions. - Optimize data systems for performance, reliability, and scalability. - Collaborate with cross-functional teams to understand data requirements and deliver efficient solutions. - Ensure data quality, consistency, and integrity across all systems and pipelines. - Implement data governance, privacy, and security best practices. - Monitor and troubleshoot data flows and pipelines to ensure high availability and minimal downtime. - Document data architecture, workflows, and system designs for maintainability and scalability. Required Technical Skills: Must Have Skills: - Strong proficiency in Python programming and SQL. - Hands-on experience in ETL design and development using tools like AWS Glue, Apache Airflow, or Talend. - Expertise in AWS Cloud Services such as S3, Redshift, Lambda, and Glue. - Experience with Big Data frameworks like Apache Spark, Hadoop, or Kafka. - Strong understanding of data modeling, data warehousing, and data architecture principles. - Proficiency in Git version control and CI/CD automation pipelines. Good to Have Skills: - Exposure to GCP or Azure cloud platforms. - Familiarity with data orchestration tools and data governance frameworks. - Experience working with structured and unstructured data at scale. Professional Attributes: - Excellent problem-solving and analytical thinking skills. - Strong communication and collaboration skills across teams. - Proven ability to deliver end-to-end data solutions with minimal supervision. - Detail-oriented mindset with a focus on data quality and automation. About the Company: [Omitting this section as it was not provided in the Job Description] Educational Qualification: - Bachelors or Masters degree in Computer Science, Engineering, Informa
