_{06th February, 2025}

Your Role:
The ideal candidate for the Senior Data Engineer position will have a strong background in AWS and PostgreSQL database management, with a passion for building and maintaining data pipelines. This role involves working closely with different stakeholders to ensure that our data infrastructure is robust, efficient, and scalable. We embrace and accept individual experiences and backgrounds to achieve a diverse and inclusive workplace.
 
Responsibilities

• Data Pipeline Development: design, build, and launch new data extraction, transformation, and loading processes.
• AWS Integration: Leverage AWS services (e.g., S3, Redshift, Glue, Lambda) to create and optimize data workflows, ensuring data availability and reliability.
• Database Management: Manage and optimize PostgreSQL databases, including schema design, indexing, and query performance tuning.
• Documentation: Maintain comprehensive documentation of data processes, architectures, and workflows.
• Troubleshooting: Diagnose and resolve data-related issues, ensuring minimal disruption to data services.
• Support: Support existing processes running in production and implement optimized solutions with limited guidance

• Bachelor’s degree in computer science, Data Science, Data Engineering, or similar areas of study, or a directly related field with 2-5 years of work experience.
• Exceptional ability to assess and communicate requirement to IT stakeholders.
• Proven experience in design, implementation, and operations of data model, AWS infrastructure, schema design, and database management.
• Familiar with industry best practice around data governance and cyber security.
• BI Tools: Familiarity with Business Intelligence tools such as Power BI.
• Data Modeling: Understanding of data modeling techniques and best practices.
• Ability to travel 5-10%.
• Key Technical Skills:
• AWS Services: Proficiency in AWS services like S3, Redshift, Glue, Lambda, and IAM.
• Database Management: Strong experience with PostgreSQL, including query optimization and database administration.
• Programming Languages: Proficiency in Python and SQL for data manipulation and automation.
• ETL Tools: Experience with ETL tools and frameworks for data integration and transformation.
• Data Warehousing: Knowledge of data warehousing concepts and practices.
• Version Control: Familiarity with version control systems such as Git/GitLab.
• Enterprise Resource Planning (ERP): SAP ECC, SAP HANA, SAP BW.

• Hybrid Schedule
• 401K
• Medical 
• Prescription Drug
• Dental 
• Vision  
• Short and Long Term Disability 
• Life and AD&D Insurance 
• Paid Vacation and Paid Holidays 
• Paid Maternity and Parental Leave 
• Employee Assistance Program