Database Architect (Cloud) for SRA
Designs and optimizes cloud-based database architectures for petabyte-scale biomedical datasets, implementing partitioning, sharding, and query tuning. Requires 5+ years experience with SQL, cloud services, Linux scripting, and production database operations.
Duties & Responsibilities
- Design and optimize cloud-based database architectures to support petabyte-scale biomedical datasets.
- Implement and manage database partitioning, sharding, and replication strategies to ensure performance, scalability, and reliability.
- Tune queries, schemas, and indexing strategies for high-throughput workloads.
- Support production-level data operations in complex, high-availability environments.
- Work with cross-functional teams to integrate cloud-native data services with pipelines and APIs.
- Troubleshoot database performance issues and implement proactive monitoring solutions.
Core Expertise
- 5+ years of professional database experience with large, distributed, or cloud-hosted databases.
- Advanced proficiency in SQL: schema design, query optimization, indexing, stored procedures.
- Deep knowledge of database partitioning and sharding strategies in cloud environments.
- Hands-on experience with Linux/UNIX environments and scripting (Bash, Python).
- Familiarity with cloud database services (AWS RDS, Aurora, Athena, Google BigQuery, or equivalent).
- Experience operating databases in production with high concurrency and large-scale data ingestion.
- Strong troubleshooting skills for performance bottlenecks, query execution plans, and distributed systems.
Preferred Qualifications
- Experience with Microsoft SQL Server and advanced features (partitioning, indexing strategies).
- Familiarity with bioinformatics databases or large scientific datasets.
- Experience with containerized workloads (Docker) and orchestration (Kubernetes).
- Knowledge of XML schemas and structured/unstructured data integration.
- Exposure to Data Warehouse, Data Lake, or Data Lakehouse concepts.
- Interest in learning Big Data platforms (Apache Spark, Hadoop) and data science tools (Jupyter).
- Proficiency in additional programming languages (Python, C++).
Salary
$120,000 - $160,000
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