Role Summary:
We are seeking a highly experienced and results-driven Senior Data System Engineer with 6+ years of expertise in architecting, building, and optimizing large-scale data infrastructure. The ideal candidate will lead the design and implementation of scalable, high-performance data platforms that support enterprise analytics, business intelligence, and data science initiatives
Key Responsibilities:
1. Data Architecture & Pipeline Leadership
- Architect, design, and maintain enterprise-grade ETL/ELT data pipelines using tools such as Apache NiFi, Talend, or similar platforms.
- Lead the development of scalable batch and real-time data ingestion frameworks.
- Standardize and optimize data integration processes across multiple systems.
- Implement robust orchestration, monitoring, and alerting mechanisms for data workflows.
- Drive performance tuning and scalability improvements for high-volume data processing.
2. Big Data & Distributed Systems Engineering
- Design and manage distributed data processing frameworks using Hadoop and Spark.
- Develop and optimize complex Spark jobs (PySpark/Scala) for large-scale transformations.
- Ensure efficient data partitioning, indexing, and storage strategies.
- Oversee cluster management, resource allocation, and performance optimization.
- Evaluate and implement modern big data technologies aligned with business needs.
3. Database & Data Warehouse Architecture
- Design scalable relational and NoSQL database architectures.
- Optimize complex SQL queries and implement advanced indexing strategies.
- Lead the development and optimization of enterprise data warehouses using Snowflake, Redshift, or similar platforms.
Required Qualifications:
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
- 6+ years of experience in data engineering, big data, or data systems roles.
- Strong hands-on experience with ETL tools (Apache NiFi, Talend, or similar).
- Deep expertise in Hadoop and Spark (PySpark/Scala).
- Advanced SQL skills with experience in performance tuning and optimization.
- Experience with relational and NoSQL databases (MongoDB, Cassandra, etc.).
- Extensive experience with enterprise data warehousing platforms such as Snowflake or Redshift.
- Proven experience working with cloud data platforms (AWS, Azure, or GCP).
Preferred Qualifications:
- Experience with real-time streaming technologies (Kafka, Flink).
- Strong programming skills in Python, Shell, or Scala.
- Experience with containerization and orchestration tools (Docker, Kubernetes).
- Knowledge of DevOps practices, CI/CD, and infrastructure automation.
- Experience designing secure and compliant enterprise data environments.
- Prior experience leading projects or mentoring teams.
Key Competencies:
- Strong architectural thinking and system design expertise.
- Excellent problem-solving and performance optimization skills.
- Ability to manage multiple complex data initiatives.
