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Chief Data Architect

2 weeks ago

Tiruchi, Tamil Nadu, India beBeeDataEngineer Full time ₹ 1,00,00,000 - ₹ 2,00,00,000
Data Engineer Role

We are seeking a highly skilled Data Engineer to join our dynamic data team. As a key member of our data infrastructure team, you will design, develop, and maintain robust data pipelines, data warehouses, and analytics platforms that serve as the backbone of our digital marketing product development.

In this role, you will collaborate with cross-functional teams including Data Scientists, Product Managers, and Marketing Technology specialists to ensure seamless data flow from various marketing channels, ad platforms, and customer touchpoints to our analytics dashboards and reporting systems. You'll be responsible for building scalable, reliable, and efficient data solutions that can handle high-volume marketing data processing and real-time campaign analytics.

Key Responsibilities:
  • Data Pipeline Development: Design, build, and maintain robust, scalable data pipelines and ETL/ELT processes
  • Data Ingestion Frameworks: Develop data ingestion frameworks to collect data from various sources (databases, APIs, files, streaming sources)
  • Data Transformation and Cleaning: Implement data transformation and cleaning processes to ensure data quality and consistency
  • Optimization and Maintenance: Optimize data pipeline performance and reliability, and perform regular maintenance and optimization of data systems
Data Infrastructure Management:
  • Data Warehouse Architecture: Design and implement data warehouse architectures
  • Database Systems: Manage and optimize database systems (SQL and NoSQL)
  • Data Lake Solutions: Implement data lake solutions and data governance frameworks
  • Data Security and Compliance: Evaluate data security, privacy, and compliance with regulatory requirements
Data Modeling and Architecture:
  • Data Modeling: Design and implement data models for analytics and reporting
  • Data Documentation: Create and maintain data dictionaries and documentation
  • Data Schemas: Develop data schemas and database structures
  • Data Versioning: Implement data versioning and lineage tracking
Collaboration and Support:
  • Collaboration: Work closely with Data Scientists, Analysts, and Business stakeholders
  • Tech Support: Provide technical support for data-related issues and queries
Monitoring and Maintenance:
  • Monitoring: Implement monitoring and alerting systems for data pipelines
  • Performance Tuning: Conduct performance tuning and capacity planning