Data Engineer

About the job
Responsibilities:

Data Pipeline Development: Design, build, and maintain data pipelines for collecting and processing marketing data.
Data Integration: Ensure seamless integration of data from various sources, including marketing platforms and databases.
Data Warehousing: Manage and optimize data warehousing solutions for efficient data storage and retrieval.
ETL (Extract, Transform, Load): Develop ETL processes to cleanse, transform, and load data into data stores.
Database Management: Administer databases, ensuring data integrity and performance.
Streaming Data: Handle real-time data streams for immediate insights and actions.
Data Quality Assurance: Implement data quality checks and validation processes.
Data Architecture: Design scalable and efficient data architectures to support analytics and reporting needs.
Data Governance: Establish data governance policies and procedures to maintain data quality and security.
Cloud Services: Utilize cloud platforms (e.g., GCP, AWS, Azure) for scalable data storage and processing.
Automation: Develop automation scripts and tools for routine data tasks.
Collaboration: Collaborate with data scientists, analysts, and other teams to provide accessible and reliable data.
Performance Optimization: Optimize data infrastructure for speed and cost-effectiveness.
Data Security: Implement security measures to protect sensitive data.
Documentation: Document data processes and workflows for reference and compliance.
Monitoring and Maintenance: Monitor data pipelines and resolve issues promptly to minimize downtime.
Scalability: Plan for future data growth and scalability needs.
Compliance: Ensure data handling adheres to relevant data protection regulations.
Cost Management: Optimize data-related costs and resource usage.

Skills:

Google BigQuery
SQL, DBMS tools of Google Cloud
AWS and Azure, Cloud Pipelining
Datalake, CDP, Data Warehouse