Description
Position Description: Responsible for designing, building, and maintaining data pipelines and
infrastructure to support data-driven decisions and analytics. The individual is responsible for the
following tasks:
A. Design, develop and maintain data pipelines, and extract, transform, load (ETL) processes to collect,
process and store structured and unstructured data
B. Build data architecture and storage solutions, including data lakehouses, data lakes, data warehouse,
and data marts to support analytics and reporting
C. Develop data reliability, efficiency, and qualify checks and processes
D. Prepare data for data modeling
E. Monitor and optimize data architecture and data processing systems
F. Collaboration with multiple teams to understand requirements and objectives
G. Administer testing and troubleshooting related to performance, reliability, and scalability
H. Create and update documentation
Role and Responsibilities: Design and implement robust, scalable data models to support the application, analytics and
business intelligence initiatives.
Optimize data warehousing solutions and manage data migrations in the AWS ecosystem,
utilizing Amazon Redshift, RDS, and DocumentDB services.
Develop and maintain scalable ETL pipelines using AWS Glue and other AWS services to
enhance data collection, integration, and aggregation.
Ensure data integrity and timeliness in the data pipeline, troubleshooting any issues that arise
during data processing.
Integrate data from various sources using AWS technologies, ensuring seamless data flow across
systems.
Collaborate with stakeholders to define data ingestion requirements and implement solutions to
meet business needs.
Monitor, tune, and manage database performance to ensure efficient data loads and queries.
Implement best practices for data management within AWS to optimize storage and computing
costs.
Ensure all data practices comply with regulatory requirements and department policies.
Implement and maintain security measures to protect data within AWS services.
Lead and mentor junior data engineers and team members on AWS best practices and technical
challenges.
Collaborate with UI/API team, business analysts, and other stakeholders to support data-driven
decision-making.
