Senior Data Base Administrator

Responsibilities

Ownership in installations, creation, management, monitoring, scaling and tuning RDMBS and NoSQL databases for various business units.

Day to day management activities of production databases for online system operations including monitoring, troubleshooting, backup, restore, change management, and storage management

Development of stored procedures, packages, triggers, SQL queries, reports, forms and scripts.

Responsible for Database Replay, Partitioning, DB Sharding, Schema Management, Transaction management, Caching and Pooling, Resiliency, Case sensitive passwords, Virtual columns and Security.

Run performance and tuning tools such as ASH, AWR, and STATSPACK.

Participate in discussions and recommend new strategies for installation, upgrade, configuration, and patching of new and existing RDBMS infrastructure (Oracle & MySql) and NoSQL infrastructure (MongoDB & Cassandra).

Recommend new strategies and architectures for high availability, monitoring, database security, backup, and recovery for large scale databases

You will be working with AWS RDS & Dynamo DB.

Required Skills/Experience

Bachelor's degree in Computer Science or equivalent is preferred

10+ years of DBA experience in RDMBS (Oracle, MySQL, PL/SQL).

5+ years of experience in NoSQL such as Cassandra and MongoDB

Expertise in JSON document modeling and data transformation (XML, JSON, CSV, RDBMS)

Expertise in development of stored procedures, packages, triggers, SQL queries, reports, forms and scripts.

Expertise in Database Replay, Partitioning, DB Sharding, Schema Management, Transaction management, Caching and Pooling, Resiliency, Case sensitive passwords, Virtual columns and Security.

Good understanding of service (canonical) schema, forward and reverse model engineering, Data Flow Diagraming

Hands on experience with various performance and tuning tools such as ASH, AWR, STATSPACK, EXPLAINS PLAN, SQL TRACE, TKPROF and ADDM reports.

Strong background in Data Management Best Practices, Data Integration, Data Rationalization and Data Patterns

Strong understanding in the principles of Data warehousing using Fact Tables, Dimension Tables, star schema modeling and snowflake schema modeling, Slowly changing dimensions, foreign key concepts, referential integrity.

Scripting language skills such as Perl, Python, and Bash is a strong plus

Experience in Hadoop Big Data environment (Hive, Pig, Map Reduce) is a big plus

Strong verbal/written communication and data presentation skills, including an ability to effectively communicate with both business and technical teams