Optum Global Solutions Data Engineer Interview Questions and Answers

Apache Spark is a distributed data processing framework designed for speed and ease of use.

• Core Components: Spark consists of the Spark Core, Spark SQL, Spark Streaming, MLlib, and GraphX.

• Cluster Manager: Spark can run on various cluster managers like YARN, Mesos, or Kubernetes.

• Resilient Distributed Datasets (RDDs): RDDs are the fundamental data structure in Spark, enabling fault tolerance and parallel processing.

• ...read more

I manage my work by prioritizing tasks, setting goals, staying organized, and communicating effectively with team members.

• Prioritize tasks based on deadlines and importance

• Set clear goals and milestones to track progress

• Stay organized with tools like project management software

• Communicate effectively with team members to ensure alignment and collaboration

ADF in Azure stands for Azure Data Factory, a cloud-based data integration service that allows you to create, schedule, and manage data pipelines.

• Azure Data Factory (ADF) is used to orchestrate and automate data movement and data transformation.

• It supports a wide range of data sources, including Azure Blob Storage, Azure SQL Database, and on-premises data sources.

• ADF allows you to create data pipelines using a vis...read more

Understanding SQL joins is crucial for data engineers to combine data from multiple tables effectively.

• INNER JOIN: Returns records with matching values in both tables. Example: SELECT * FROM A INNER JOIN B ON A.id = B.id;

• LEFT JOIN: Returns all records from the left table and matched records from the right table. Example: SELECT * FROM A LEFT JOIN B ON A.id = B.id;

• RIGHT JOIN: Returns all records from the right tabl...read more

SQL window functions allow for calculations over a specific subset of data.

• Window functions are used to perform calculations over a specific subset of data

• They are used with the OVER() clause and can be used with aggregate functions

• Examples include ROW_NUMBER(), RANK(), and LAG()

• They are useful for calculating running totals, rankings, and comparing values across rows

SQL CASE conditions allow for conditional logic in queries, enabling dynamic data manipulation based on specific criteria.

• CASE can be used in SELECT statements to create new columns based on conditions. Example: SELECT name, CASE WHEN age < 18 THEN 'Minor' ELSE 'Adult' END AS age_group FROM users;

• It can also be used in ORDER BY clauses to sort data conditionally. Example: SELECT name, score FROM students ORDER ...read more