We are looking for a Senior Data Engineer to assist our client in the telecommunications space. The client is using Sisense to embed BI dashboards into their SaaS platform. Their core production data, which Sisense reads from, is housed in PostgreSQL databases within their AWS cloud environment. This data is periodically read into a separate AWS account and region where Sisense runs the analytics, resulting in slow and costly data transmission. The client is setting up a Data Warehouse that will act as an intermediate interface between Sisense and their production data. This will improve query performance, provide greater flexibility for the BI team to optimize queries, and accelerate client change requests and new feature development.

Requirements:

• Design and implement a robust Data Warehouse solution in AWS
• Architect ETL processes to efficiently move data between the production PostgreSQL databases and the Data Warehouse
• Optimize data flow and data transformation processes to ensure efficient and cost-effective data transmission
• Integrate the Data Warehouse with Sisense to enable seamless BI dashboard embedding
• Collaborate with the BI team to refine queries and improve performance within the new Data Warehouse
• Establish best practices for data governance, security, and monitoring within the Data Warehouse

Must-Have Skills:

• Strong experience with Data Warehousing concepts and best practices
• Advanced proficiency with AWS services, including but not limited to:
  • Amazon Redshift
  • AWS Glue
  • Amazon S3
  • AWS Data Pipeline or Step Functions
  • Amazon RDS (PostgreSQL)
  • AWS IAM for security
• Proven track record in ETL development, data transformation, and data integration
• Strong SQL and query optimization skills
• Experience working with BI tools (preferably Sisense) and embedding BI dashboards into SaaS platforms
• Deep understanding of data modeling, star schema, and data normalization/denormalization principles
• Familiarity with data governance and security best practices
• Excellent communication skills to interact effectively with the BI team and other stakeholders

Nice-to-Have Skills:

• Experience in the telecommunications domain
• Familiarity with other AWS services such as: Amazon Kinesis, AWS Lambda,
• Amazon QuickSight. AWS Lake Formation
• Knowledge of Python or other scripting languages for data processing
• Familiarity with other BI tools like Tableau or Power BI
• Experience with DevOps tools like Docker, Terraform, and CI/CD pipelines
• Certifications in AWS, such as AWS Certified Solutions Architect or AWS Certified
• Data Analytics – Specialty

Key Attributes:

• Analytical thinker with a problem-solving mindset
• Self-driven and proactive in identifying opportunities for improvement
• Team player with the ability to work independently and collaboratively