Here are additional topics relevant for a PL/SQL Developer with 3 years of experience that might come up in interviews. These topics go beyond the basics and cover areas that demonstrate both depth of knowledge and an understanding of real-world application in PL/SQL development:

1. Dynamic SQL and EXECUTE IMMEDIATE

How to write SQL dynamically at runtime using EXECUTE IMMEDIATE.

Use cases where dynamic SQL is required (e.g., variable table names, building SQL from user input).

Differences between Native Dynamic SQL (NDS) and DBMS_SQL package.

1. Advanced Cursors (Cursor Attributes and Ref Cursors)

Using cursor attributes like %FOUND, %NOTFOUND, %ROWCOUNT, and %ISOPEN.

Working with REF CURSORs (variable cursors), which can be passed as parameters, useful for dynamic result sets.

Cursor lifecycle management for optimized memory usage.

1. Composite Data Types (Records and Collections)

Using PL/SQL RECORD and nested tables, associative arrays, and VARRAYs.

Complex record structures with nested collections.

Scenarios where you’d use collections for efficient data processing.

1. Error Handling and Exception Propagation

Advanced exception handling techniques, such as nested exception blocks and propagation.

Custom exception handling and using RAISE_APPLICATION_ERROR.

Logging and debugging techniques using DBMS_OUTPUT and custom logging mechanisms.

1. Bulk Data Processing (BULK COLLECT and FORALL)

Using BULK COLLECT and FORALL effectively for performance optimization.

Error handling with SAVE EXCEPTIONS in FORALL.

When to use LIMIT with BULK COLLECT to manage memory.

1. Triggers: Types and Advanced Usage

Different types of triggers (row-level, statement-level, BEFORE, AFTER triggers).

Compound triggers for handling mutating table errors.

Triggers for auditing, enforcing business rules, and complex validations.

1. Performance Tuning and Optimization Techniques

Tips for writing efficient PL/SQL code (e.g., minimizing context switches, avoiding unnecessary loops).

Using EXPLAIN PLAN and Oracle's AUTOTRACE to identify bottlenecks.

Optimization of recursive and multi-level nested queries.

1. Partitioning and Partition-Aware PL/SQL Code

Understanding and implementing table partitioning strategies.

Writing PL/SQL code that takes advantage of partitioning (e.g., pruning).

Benefits of partitioning for large data sets.

1. Data Integrity Constraints and Referential Integrity

Enforcing data integrity using constraints (NOT NULL, UNIQUE, CHECK, FOREIGN KEY).

Scenarios where PL/SQL code might supplement constraints.

How to manage constraint violations in PL/SQL.

1. Oracle Packages (DBMS and UTL) for Utility Functions

Using Oracle-supplied packages like DBMS_JOB, DBMS_SCHEDULER, UTL_FILE, DBMS_OUTPUT, and DBMS_LOB.

File handling with UTL_FILE (reading/writing files on the server).

Scheduled jobs with DBMS_SCHEDULER.

1. Advanced PL/SQL Features: Autonomous Transactions

Using PRAGMA AUTONOMOUS_TRANSACTION for managing transactions independently.

Scenarios such as logging errors within autonomous transactions.

Considerations for committing inside autonomous transactions.

1. Materialized Views and Refresh Strategies

Creating materialized views and understanding refresh mechanisms (FAST, COMPLETE).

Using materialized views to improve query performance in PL/SQL.

Handling refresh timing and performance implications.

1. Data Warehousing Concepts (ETL in PL/SQL)

Loading and transforming large datasets (Extract, Transform, Load).

Using PL/SQL collections for ETL and bulk processing.

Handling data staging, aggregation, and summarization.

1. PL/SQL Debugging and Exception Logging

Debugging techniques and tools like DBMS_DEBUG and SQL Developer Debugger.

Writing custom logging procedures for tracking errors in complex applications.

Using EXCEPTION_INIT to associate error numbers with user-defined exceptions.

1. Working with XML and JSON Data in PL/SQL

Using Oracle functions to parse and generate XML (e.g., XMLTYPE).

Working with JSON data using Oracle’s JSON functions (e.g., JSON_QUERY, JSON_VALUE).

Scenarios where XML and JSON handling are beneficial for integration.

1. PL/SQL Best Practices and Code Standards

Writing modular, readable, and maintainable PL/SQL code.

Following naming conventions, commenting, and error-handling standards.

Strategies for reusable code (modular functions/procedures, utility packages).

1. Advanced DML with MERGE Statement

Using the MERGE statement for conditional inserts, updates, and deletes.

Scenarios where MERGE improves performance for batch operations.

Error handling and logging in MERGE operations.

1. Database Links and Distributed Transactions

Creating and using database links to access data across different databases.

Handling distributed transactions and ensuring data consistency.

Security and performance considerations with database links.

1. Working with Large Objects (LOBs)

Managing large objects (e.g., CLOBs, BLOBs) in PL/SQL.

Using DBMS_LOB package functions to manipulate LOB data.

Performance considerations and memory management with large objects.

1. Refactoring and Modularization in PL/SQL

Refactoring large code blocks into modular procedures and functions.

Techniques for reducing redundancy and improving code readability.

Benefits of modular PL/SQL code for maintainability and debugging.

These topics cover a wide range of real-world skills and practices that are expected from a PL/SQL Developer with three years of experience. Being prepared on these topics will help you demonstrate expertise in writing efficient, scalable, and maintainable PL/SQL code while handling complex business requirements and data management tasks.