IBM Data Engineer Interview Questions, Process, and Tips for Experienced

Optimisation in code involves improving efficiency and performance.

• Use of efficient data structures and algorithms

• Minimizing unnecessary computations

• Reducing memory usage

• Parallel processing for faster execution

• Profiling and identifying bottlenecks

Spark optimizations techniques improve performance and efficiency of Spark jobs.

• Partitioning data to optimize parallelism

• Caching data in memory to avoid recomputation

• Using broadcast variables for small lookup tables

• Avoiding shuffles by using narrow transformations

• Tuning memory and executor settings for optimal performance

CS Workflows refer to the processes and steps involved in managing and analyzing data in a computer science context.

• CS Workflows involve defining data sources and transformations

• They often include data cleaning, processing, and analysis steps

• Tools like Apache Airflow and Luigi are commonly used for managing workflows

• CS Workflows help automate data pipelines and ensure data quality and consistency

Forms and Templates are used in workflow and web reports to standardize data input and presentation.

• Forms are used to collect data in a structured manner, often with predefined fields and formats

• Templates are pre-designed layouts for presenting data in a consistent way

• Forms and Templates help streamline processes, ensure data consistency, and improve reporting accuracy

• In workflow management, Forms can be used to gather...read more

The interview questions cover project architecture, complex job handling, lookup types, SCD-2 implementation, SQL analytical functions, and Unix commands.

• Project architecture involves designing the overall structure of a data project.

• Complex job handling refers to managing intricate data processing tasks within a project.

• Lookup types include exact match, range match, and fuzzy match.

• SCD-2 implementation in DataStage in...read more