Job Summary: We are looking for a skilled Data Engineer with strong hands-on experience in AWS to design, build, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have expertise in modern data warehousing, ETL/ELT development, and distributed data processing while ensuring data quality, performance, and security. Key Responsibilities: ·      Design, develop, and maintain scalable data pipelines using AWS services. ·      Build and optimize ETL/ELT workflows for structured and unstructured data. ·      Implement data lakes and data warehouses on AWS. ·      Work with large datasets to ensure high performance, reliability, and data integrity. ·      Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements. ·      Perform data modeling for analytical and operational use cases. ·      Ensure data quality, governance, and security best practices. ·      Monitor and troubleshoot data workflows and production issues. ·      Support CI/CD and automation for data platform deployments. Required Skills & Experience: ·      Strong hands-on experience with AWS services such as S3, Glue, Redshift, Lambda, EMR, Athena, and RDS. ·      Proficiency in Python and SQL for data processing and analysis. ·      Experience in building and optimizing ETL/ELT pipelines. ·      Solid understanding of data warehousing and data lake architecture. ·      Experience with Apache Spark / PySpark. ·      Knowledge of workflow orchestration tools (Airflow or similar). ·      Familiarity with streaming frameworks (Kinesis/Kafka) is a plus. ·      Experience with data modeling and performance tuning. ·      Understanding of DevOps, CI/CD, and infrastructure as code (Terraform/CloudFormation). ·      Experience working in Agile/Scrum environments. Good to Have: ·      Experience with Snowflake on AWS. ·      Exposure to real-time data processing. ·      AWS certification (e.g., AWS Certified Data Analytics / Solutions Architect). Soft Skills: ·      Strong problem-solving and analytical skills. ·      Excellent communication and stakeholder management. ·      Ability to work in a fast-paced, collaborative environment.

Job Summary: We are looking for a skilled Data Engineer with strong hands-on experience in AWS to design, build, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have expertise in modern data warehousing, ETL/ELT development, and distributed data processing while ensuring data quality, performance, and security. Key Responsibilities: ·      Design, develop, and maintain scalable data pipelines using AWS services. ·      Build and optimize ETL/ELT workflows for structured and unstructured data. ·      Implement data lakes and data warehouses on AWS. ·      Work with large datasets to ensure high performance, reliability, and data integrity. ·      Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements. ·      Perform data modeling for analytical and operational use cases. ·      Ensure data quality, governance, and security best practices. ·      Monitor and troubleshoot data workflows and production issues. ·      Support CI/CD and automation for data platform deployments. Required Skills & Experience: ·      Strong hands-on experience with AWS services such as S3, Glue, Redshift, Lambda, EMR, Athena, and RDS. ·      Proficiency in Python and SQL for data processing and analysis. ·      Experience in building and optimizing ETL/ELT pipelines. ·      Solid understanding of data warehousing and data lake architecture. ·      Experience with Apache Spark / PySpark. ·      Knowledge of workflow orchestration tools (Airflow or similar). ·      Familiarity with streaming frameworks (Kinesis/Kafka) is a plus. ·      Experience with data modeling and performance tuning. ·      Understanding of DevOps, CI/CD, and infrastructure as code (Terraform/CloudFormation). ·      Experience working in Agile/Scrum environments. Good to Have: ·      Experience with Snowflake on AWS. ·      Exposure to real-time data processing. ·      AWS certification (e.g., AWS Certified Data Analytics / Solutions Architect). Soft Skills: ·      Strong problem-solving and analytical skills. ·      Excellent communication and stakeholder management. ·      Ability to work in a fast-paced, collaborative environment.

Job Summary: We are looking for a skilled Data Engineer with strong hands-on experience in AWS to design, build, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have expertise in modern data warehousing, ETL/ELT development, and distributed data processing while ensuring data quality, performance, and security. Key Responsibilities: ·      Design, develop, and maintain scalable data pipelines using AWS services. ·      Build and optimize ETL/ELT workflows for structured and unstructured data. ·      Implement data lakes and data warehouses on AWS. ·      Work with large datasets to ensure high performance, reliability, and data integrity. ·      Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements. ·      Perform data modeling for analytical and operational use cases. ·      Ensure data quality, governance, and security best practices. ·      Monitor and troubleshoot data workflows and production issues. ·      Support CI/CD and automation for data platform deployments. Required Skills & Experience: ·      Strong hands-on experience with AWS services such as S3, Glue, Redshift, Lambda, EMR, Athena, and RDS. ·      Proficiency in Python and SQL for data processing and analysis. ·      Experience in building and optimizing ETL/ELT pipelines. ·      Solid understanding of data warehousing and data lake architecture. ·      Experience with Apache Spark / PySpark. ·      Knowledge of workflow orchestration tools (Airflow or similar). ·      Familiarity with streaming frameworks (Kinesis/Kafka) is a plus. ·      Experience with data modeling and performance tuning. ·      Understanding of DevOps, CI/CD, and infrastructure as code (Terraform/CloudFormation). ·      Experience working in Agile/Scrum environments. Good to Have: ·      Experience with Snowflake on AWS. ·      Exposure to real-time data processing. ·      AWS certification (e.g., AWS Certified Data Analytics / Solutions Architect). Soft Skills: ·      Strong problem-solving and analytical skills. ·      Excellent communication and stakeholder management. ·      Ability to work in a fast-paced, collaborative environment.

• Design and build robust data pipelines and feature stores that powers our AI products. • Analyse data requirements, understand complex data sources, and partner with architects to determine the best methods to extract, transform, and load data into data platform. • Lead conversations with business or functional teams to translate user requirements into reusable and cost-efficient data acquisition methodologies for AI products. • Be the key anchor for data extraction, preparation and hosting processes representing the AI team. Data expert for engineering datasets used by data scientists working on various use cases. • Perform functional and stress testing on data models and extraction jobs to ensure that design is optimized for performance, scale, and reusability. • Manage foundational data administration tasks such as scheduling jobs, troubleshooting job errors, identifying issues with job windows, assisting with database backups and performance tuning. • Ensure data quality throughout entire development process, including audits and feedback loops to sources of truth. • Create or update technical documentation for transition to support teams. • Mentor junior data engineers