- Develop and maintain scalable, reliable, and secure data pipelines and platforms using cloud-based technologies and best practices. (AWS, Snowflake, dbt)

- Integrate and transform data from various sources, such as SAP, SQL Server, S3 and APIs, Infor M3 JDE, and Salesforce.

- Optimize and monitor the performance, quality, and availability of data pipelines and platforms, ensuring data integrity and consistency.

- Maintain and support data processes on SQL Server, ensuring that data flows seamlessly and efficiently across systems.

- Troubleshoot and resolve any issues related to data integration and transformation, ensuring minimal downtime and disruption.

- Support data analysis and reporting by creating and maintaining data models, schemas, views, and dashboards using tools like Power BI, Tableau, or SSRS.

- Stay up-to-date with the latest advancements in Gen AI and contribute to research and development initiatives.

- Collaborate with data engineers, data analysts, data scientists, and business stakeholders to understand and translate business requirements into technical specifications and solutions.

- Collaborate with stakeholders across the business to understand their needs and challenges, translating them into clear, concise, and technically feasible data analysis requests.

Requirements :

- A Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- Previous experience in or with 8+ years' experience as a Software Engineer, Data Engineer, or Data Analyst.

- Experience in cloud data platforms like Snowflake.

- Automated data integration and transformation using tools such as dbt or Informatica.

- Previous programming expertise in SQL, Python.

- In-depth knowledge of AWS services, including EC2 Bedrock and S3

- Experience in managing data processes in SQL Server.

- Ability to write, debug, and optimize SQL queries.

- Strong analytical skills and the ability to combine data from different sources.

- Excellent communication and presentation skills, with the ability to explain complex data to non-technical audiences.

- User-facing written and verbal communication skills and experience.