Cloud Data Engineering Specialist - Python/SQL

As a Data Architect & Platform Developer, your primary responsibilities will involve designing and implementing robust cloud-based data architectures. This includes creating data lakes, data warehouses, and real-time streaming systems. You will be tasked with developing scalable ETL/ELT pipelines using cloud-native tools like AWS Glue, Azure Data Factory, GCP Dataflow, Databricks, or Apache Airflow. Your role will also require you to integrate structured, semi-structured, and unstructured data from various sources into centralized platforms. Your key responsibilities will include: - Designing and implementing cloud-based data architectures - Developing scalable ETL/ELT pipelines using cloud-native tools - Integrating data from various sources into centralized platforms - Building, automating, and optimizing high-performance data pipelines - Ensuring data availability, reliability, and integrity - Implementing data quality checks, validations, and monitoring frameworks - Working with cloud-native services and managing infrastructure as code - Supporting big data analytics and enabling analytics platforms - Implementing data governance practices and ensuring data security - Collaborating with stakeholders and communicating technical concepts clearly In terms of qualifications, you are required to have: - Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or related field - Expertise in one major cloud platform: AWS, Azure, or GCP - Strong programming skills in Python, SQL, Scala, or Java - Proficiency with ETL/ELT tools, data orchestration tools, and workflow scheduling frameworks - Experience with relational and NoSQL databases - Solid understanding of data modeling, warehousing concepts, and distributed systems This job will provide you with the opportunity to work on cutting-edge technologies and collaborate with various teams to drive impactful data solutions. As a Data Architect & Platform Developer, your primary responsibilities will involve designing and implementing robust cloud-based data architectures. This includes creating data lakes, data warehouses, and real-time streaming systems. You will be tasked with developing scalable ETL/ELT pipelines using cloud-native tools like AWS Glue, Azure Data Factory, GCP Dataflow, Databricks, or Apache Airflow. Your role will also require you to integrate structured, semi-structured, and unstructured data from various sources into centralized platforms. Your key responsibilities will include: - Designing and implementing cloud-based data architectures - Developing scalable ETL/ELT pipelines using cloud-native tools - Integrating data from various sources into centralized platforms - Building, automating, and optimizing high-performance data pipelines - Ensuring data availability, reliability, and integrity - Implementing data quality checks, validations, and monitoring frameworks - Working with cloud-native services and managing infrastructure as code - Supporting big data analytics and enabling analytics platforms - Implementing data governance practices and ensuring data security - Collaborating with stakeholders and communicating technical concepts clearly In terms of qualifications, you are required to have: - Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or related field - Expertise in one major cloud platform: AWS, Azure, or GCP - Strong programming skills in Python, SQL, Scala, or Java - Proficiency with ETL/ELT tools, data orchestration tools, and workflow scheduling frameworks - Experience with relational and NoSQL databases - Solid understanding of data modeling, warehousing concepts, and distributed systems This job will provide you with the opportunity to work on cutting-edge technologies and collaborate with various teams to drive impactful data solutions.