Data Architect

Role Overview: You will be responsible for designing and developing scalable data pipelines using AWS services. You will integrate diverse data sources to ensure data consistency and reliability. Collaborating with data scientists and stakeholders, you will understand data requirements and implement data security measures. Monitoring and troubleshooting data pipelines for optimal performance, you will also optimize and maintain data warehouse and data lake architectures. Additionally, creating and maintaining comprehensive documentation for data engineering processes will be part of your role. Key Responsibilities: - Proven experience with Snowflake and SQL. - Expert-level proficiency in building and managing data pipelines with Python. - Strong experience in AWS cloud services, including Lambda, S3, Glue, and other data-focused services. - Exposure to Terraform for provisioning and managing infrastructure-as-code on AWS. - Proficiency in SQL for querying and modeling large-scale datasets. - Hands-on experience with Git for version control and managing collaborative workflows. - Familiarity with ETL/ELT processes and tools for data transformation. - Strong understanding of data architecture, data modeling, and data lifecycle management. - Excellent problem-solving and debugging skills. - Strong communication and collaboration skills to work effectively in a global, distributed team environment. Qualifications Required: - Good understanding of Architecting the data and solution. - Data Quality, Governance, Data Security, and Data Modelling concepts. - Data Modelling, Mapping, and Compliance to BaDM. - Solutioning on Cloud (AWS) with cloud tools, with a good understanding of Snowflake. - Defining CI/CD config for GitHub and AWS Terraform for deployment config. - Ensuring Architecture evolution with the latest technology. - Guiding and mentoring team, reviewing code, and ensuring development to standards. Additional Details: No additional details provided in the job description. Role Overview: You will be responsible for designing and developing scalable data pipelines using AWS services. You will integrate diverse data sources to ensure data consistency and reliability. Collaborating with data scientists and stakeholders, you will understand data requirements and implement data security measures. Monitoring and troubleshooting data pipelines for optimal performance, you will also optimize and maintain data warehouse and data lake architectures. Additionally, creating and maintaining comprehensive documentation for data engineering processes will be part of your role. Key Responsibilities: - Proven experience with Snowflake and SQL. - Expert-level proficiency in building and managing data pipelines with Python. - Strong experience in AWS cloud services, including Lambda, S3, Glue, and other data-focused services. - Exposure to Terraform for provisioning and managing infrastructure-as-code on AWS. - Proficiency in SQL for querying and modeling large-scale datasets. - Hands-on experience with Git for version control and managing collaborative workflows. - Familiarity with ETL/ELT processes and tools for data transformation. - Strong understanding of data architecture, data modeling, and data lifecycle management. - Excellent problem-solving and debugging skills. - Strong communication and collaboration skills to work effectively in a global, distributed team environment. Qualifications Required: - Good understanding of Architecting the data and solution. - Data Quality, Governance, Data Security, and Data Modelling concepts. - Data Modelling, Mapping, and Compliance to BaDM. - Solutioning on Cloud (AWS) with cloud tools, with a good understanding of Snowflake. - Defining CI/CD config for GitHub and AWS Terraform for deployment config. - Ensuring Architecture evolution with the latest technology. - Guiding and mentoring team, reviewing code, and ensuring development to standards. Additional Details: No additional details provided in the job description.