Overview
At Surf Internet, the IT Team is crucial to supporting the organization’s operation. The Data Analytics Engineer is responsible for designing, developing, and maintaining scalable data pipelines and analytical frameworks. This role blends data architecture, engineering, and analytical skills to transform raw data into actionable insights that drive informed decision-making across the organization. This hybrid position typically involves:
- Designing Data Architecture: Creating scalable and efficient data frameworks.
- Building & Maintaining Pipelines: Developing and managing the systems that ingest, transform, and store data.
- Extracting Insights: Analyzing data to generate actionable insights for decision-making.
This role is ideal for individuals who thrive in a dynamic environment and are passionate about leveraging data to drive business outcomes.
Reports To: Director of IT
Department: IT
Job Status: Exempt
Responsibilities:
Data Architecture & Pipeline Development:
- Design and implement robust, scalable data architectures.
- Build, test, and maintain efficient ETL/ELT pipelines to process data from various sources.
Data Integration & Management:
- Integrate data from multiple internal and external sources.
- Optimize data models to enhance query performance and data retrieval.
- Ensure data integrity, consistency, and security through rigorous validation and quality assurance practices.
Analytics & Reporting:
- Collaborate with data scientists, analysts, and business stakeholders to understand data needs and develop tailored reporting solutions.
- Develop dashboards and visualizations to present key metrics and trends.
- Perform exploratory data analysis to identify insights that inform business strategies.
Technical Leadership & Best Practices:
- Establish and enforce best practices in data management and data engineering.
- Provide technical guidance on tool selection, system architecture, and process improvements.
- Work with cross-functional teams to troubleshoot issues and optimize data workflows.
Data Governance & Compliance:
- Ensure adherence to data governance policies and regulatory requirements.
- Implement robust security measures to protect sensitive data.
Vendor Partner Relationship Management:
- Manage relationships with vendor partners to ensure seamless integration and support for data tools and platforms.
- Evaluate and onboard new vendor solutions that align with the organization's data strategy.
