Design, model, and implement robust and scalable database solutions for both Oracle and Big Data platforms.
Performance Tuning & Optimization:
Proactively monitor, analyze, and optimize database performance for Oracle (SQL, PL/SQL, views, packages, stored procedures) and Big Data (Hive, Impala) environments. Identify and resolve bottlenecks, ensuring efficient query execution and data retrieval.
Data Ingestion & ETL:
Develop and manage efficient data ingestion pipelines using tools like Sqoop for moving data between relational databases and Hadoop.
Big Data Management:
Administer, maintain, and optimize Hadoop ecosystem components, including Hive and Impala, ensuring data availability and integrity.
Data Modeling:
Create and maintain logical and physical data models for both OLTP and analytical systems.
Troubleshooting & Support:
Provide expert-level troubleshooting and support for database-related issues, ensuring minimal downtime and business continuity.
Collaboration:
Work closely with data scientists, data analysts, developers, and other stakeholders to understand data requirements and deliver effective database solutions.
Documentation:
Create and maintain comprehensive documentation for database designs, configurations, and operational procedures.
Best Practices:
Advocate and implement database best practices, including security, backup, recovery, and disaster recovery strategies.
Reporting & Analytics Support:
Collaborate with BI teams and analysts, providing expertise on data structures and potentially supporting reporting tools like Tableau.
Required Skills & Experience:
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Minimum 5+ years of hands-on professional experience
in database administration, development, or engineering roles.
Proficiency in Oracle Database:
+ Extensive experience with Oracle SQL, PL/SQL, views, packages, and stored procedures.
+ Proven ability in Oracle query tuning, performance optimization, and index management.
+ Familiarity with Oracle database architecture, backup/recovery, and security concepts.
Strong Big Data Ecosystem Knowledge:
+ Demonstrable experience with Hadoop and its core components.
+ Expertise in Hive for data warehousing and query processing.
+ Experience with Impala for real-time querying of data in Hadoop.
+ Solid understanding of data ingestion tools like Sqoop for RDBMS-to-Hadoop data transfer.
Data Warehousing & ETL Concepts:
Strong understanding of data warehousing principles, dimensional modeling, and ETL processes.
Analytical & Problem-Solving Skills:
Excellent analytical, problem-solving, and debugging skills with a keen eye for detail.
Communication:
Strong verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Desired (Good to Have) Skills:
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Tableau or other BI Tools:
Experience working with Tableau (dashboard development, data source connectivity, performance optimization) or similar business intelligence tools is a significant plus.
Other NoSQL Databases:
Exposure to other NoSQL databases (e.g., Cassandra, MongoDB) is beneficial.
Cloud Platforms:
Experience with database services on cloud platforms (AWS, Azure, GCP).
Scripting Languages:
Proficiency in scripting languages such as Python or Shell scripting for automation and data manipulation.
Version Control:
Familiarity with version control systems (e.g., Git).
Agile Methodologies:
Experience working in an Agile/Scrum development environment.
Education:
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Bachelor's or Master's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
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Job Family Group:
Technology
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Job Family:
Applications Development
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Time Type:
Full time
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Most Relevant Skills
Please see the requirements listed above.
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Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
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