Key Responsibilities:

• Database Design & Development: 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:

• 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:

• 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:

• 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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