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Senior Data Platform Engineer
2 months ago
About the Role
We are seeking a highly skilled Senior Data Platform Engineer to join our team at CodeX Tech-IT LLC. As a key member of our data engineering team, you will play a critical role in building and scaling our data platform to support complex data processing and analytics needs.
Key Responsibilities
- Design and develop a scalable and reliable data platform that supports batch processing, real-time data streams, and advanced analytics.
- Ensure the platform can handle the growing needs of the business in a cost-efficient and performance-optimized manner.
Data Pipeline Management
- Develop and manage ETL/ELT pipelines to support data ingestion, transformation, and distribution across the organization.
- Ensure that these pipelines are scalable, resilient, and optimized for performance.
Real-Time Data Processing
- Design and implement real-time data processing solutions using tools like Apache Kafka and Apache Flink, ensuring low-latency, high-throughput data streams for business-critical applications.
Data Storage Optimization
- Lead the design and optimization of data lakes and data warehouses.
- Ensure efficient data storage, retrieval, and cost management in cloud environments.
System Reliability and Monitoring
- Implement monitoring solutions and data quality frameworks to ensure the accuracy, reliability, and security of data.
- Proactively identify and resolve performance bottlenecks and data pipeline issues.
Collaboration and Cross-Team Support
- Collaborate with data scientists, analysts, and product teams to understand business requirements and deliver scalable data solutions.
- Ensure that the platform supports both current and future data use cases.
Requirements
- 7+ years of hands-on experience in data platform engineering, with expertise in architecting and maintaining scalable data platforms.
- Proven experience designing and implementing both batch and real-time data pipelines in cloud environments (AWS preferred).
- Deep expertise in distributed data processing frameworks (e.g., Apache Spark, Presto) and real-time streaming technologies (Kafka, Flink).
- Experience with modern data lake architectures and table formats like Hudi, Iceberg, or Delta Lake.
- Strong hands-on programming skills in Python and/or Java, with the ability to build robust, scalable, and maintainable code for complex data systems.
- Hands-on SQL and/or NoSQL experience.
- Hands-on experience with Infrastructure as Code (Terraform or Ansible) for managing cloud infrastructure.
- Experience in performance tuning and optimization of large-scale data systems.
- Proficient in scoping and prioritizing tasks, focusing on delivering incremental improvements, while remaining flexible and responsive to evolving project needs.
- Excellent communication and leadership skills, with a track record of mentoring junior engineers.
- Bachelor's/Master's degree in Computer Science, Engineering, or a related field.
Preferred Qualifications
- Experience with DataOps and CI/CD pipelines in data engineering.
- Experience in building data platforms from bottom up.
- Knowledge of Kubernetes is a significant plus.
- Experience in a startup environment, with a willingness to innovate and adapt to changing business needs.
