Data Engineer 1
30+ Data Engineer 1 Interview Questions and Answers

Asked in UKG

Q. Describe a time when you optimized a SQL query and how you approached it.
I optimized a slow SQL query by analyzing execution plans and indexing key columns, resulting in a significant performance boost.
Identified slow query using monitoring tools like SQL Profiler.
Analyzed the execution plan to find bottlenecks, such as table scans.
Added indexes on frequently queried columns, improving lookup speed.
Rewrote the query to use JOINs instead of subqueries for better performance.
Tested the optimized query against the original to measure performance gain...read more

Asked in Tech Mahindra

Q. What are joins and their types? How many columns will there be after performing each type of join?
Joins are used to combine rows from two or more tables based on a related column between them.
Types of joins include inner join, outer join (left, right, full), and cross join.
Number of columns after join depends on the type of join and the columns being selected.
For example, an inner join will only include rows that have matching values in both tables, resulting in a combined table with columns from both tables.
A left outer join will include all rows from the left table and ...read more

Asked in Ingram Micro

Q. What different kinds of views can be created?
Different kinds of views that can be created include materialized views, virtual views, and dynamic views.
Materialized views store the result set of a query physically and are updated periodically.
Virtual views are based on SQL queries and do not store data physically.
Dynamic views are created on the fly based on user input or system conditions.
Other types of views include read-only views, updatable views, and recursive views.

Asked in VDA Infosolutions

Q. What are the primary components of data architecture?
Data consists of various components including types, structures, sources, and formats that define its usability and context.
Types: Data can be structured (e.g., databases), semi-structured (e.g., JSON, XML), or unstructured (e.g., text, images).
Sources: Data can originate from various sources like sensors, user inputs, transactions, or external APIs.
Formats: Common data formats include CSV, JSON, XML, and Parquet, each serving different use cases.
Quality: Data quality compone...read more

Asked in Hoonartek

Q. How many types of triggers are there in ADF?
There are two types of triggers in Azure Data Factory: Schedule-based triggers and Event-based triggers.
Schedule-based triggers are based on a time schedule and can be set to run at specific intervals.
Event-based triggers are triggered by events such as the completion of a pipeline run or the arrival of new data.
Triggers can be used to automate the execution of pipelines in Azure Data Factory.

Asked in Accenture

Q. How many types of integration runtimes are there?
There are three types of integration runtime: Self-hosted, Azure, and SSIS
Self-hosted integration runtime is installed on a local machine or a virtual machine within an on-premises network
Azure integration runtime is managed by Azure Data Factory and runs in the Azure cloud
SSIS integration runtime is used to run SQL Server Integration Services packages in Azure Data Factory
Data Engineer 1 Jobs




Asked in Concentrix Catalyst

Q. Describe a PySpark scenario to remove regex characters from column values.
Use Pyspark to remove regex characters from column values
Use the regexp_replace function in Pyspark to remove regex characters from column values
Specify the regex pattern to match and the replacement string
Apply the regexp_replace function to the desired column in the DataFrame

Asked in HP India

Q. How would you handle a conflict of interest?
Handling conflicts of interest involves transparency, communication, and prioritizing ethical considerations.
Acknowledge the conflict openly and honestly
Communicate with all parties involved to understand perspectives
Prioritize ethical considerations and make decisions based on what is best for all stakeholders
Seek guidance from a supervisor or ethics committee if necessary
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Asked in Merilytics

Q. Which is your favorite programming language?
My favorite programming language is Python because of its readability, versatility, and extensive libraries.
Python is known for its readability, making it easier to write and maintain code.
Python is versatile and can be used for web development, data analysis, machine learning, and more.
Python has a vast collection of libraries like NumPy, Pandas, and Matplotlib that make data manipulation and visualization easier.

Asked in VDA Infosolutions

Q. Explain the difference between Layer 2 and Layer 3 switches.
Layer 2 switches operate at the data link layer, while Layer 3 switches operate at the network layer, enabling routing capabilities.
Layer 2 switches use MAC addresses to forward data within the same network segment.
Layer 3 switches use IP addresses to route data between different networks.
Layer 2 switches are typically used in local area networks (LANs), while Layer 3 switches are used in larger networks or for inter-VLAN routing.
Example of Layer 2 switch: Cisco Catalyst 2960...read more

Asked in UKG

Q. Describe a time you debugged a failing ETL pipeline.
I collaborated with a team to identify and resolve issues in a failing ETL pipeline, ensuring data integrity and timely delivery.
Identified the failure point in the ETL pipeline by analyzing logs and error messages.
Collaborated with data engineers to review the transformation logic that was causing data discrepancies.
Implemented a temporary fix to reroute data while a permanent solution was developed.
Conducted a root cause analysis to prevent future occurrences, leading to im...read more

Asked in Apexon

Q. What is the difference between Azure Storage and Azure Data Lake Storage?
Azure Storage is a general-purpose storage solution, while Azure Data Lake Storage is optimized for big data analytics.
Azure Storage supports various data types (blobs, files, queues, tables) for general use cases.
Azure Data Lake Storage is designed specifically for big data analytics and supports hierarchical namespace.
Data Lake Storage allows for fine-grained access control and integrates seamlessly with Azure analytics services like Azure Databricks.
Example: Use Azure Blob...read more

Asked in Consero Global Solutions

Q. Write a SQL query that uses aggregate and window functions to solve a problem.
Understanding SQL aggregates and window functions for data analysis.
Aggregates like SUM, AVG, COUNT help summarize data.
Window functions like ROW_NUMBER() allow calculations across rows.
Example: SELECT department, AVG(salary) FROM employees GROUP BY department.
Example: SELECT employee_id, salary, ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS rank FROM employees.

Asked in HCL Group

Q. How did you use Python in your project?
Python is used in our project for data processing, analysis, and visualization.
Python is used for data cleaning and transformation tasks.
Python libraries like Pandas and NumPy are used for data manipulation.
Python is used for creating data visualizations using libraries like Matplotlib and Seaborn.

Asked in JLL Technologies

Q. What is the difference between a dictionary and a list?
A dictionary is a collection of key-value pairs, while a list is a collection of ordered elements.
A dictionary is accessed by keys, while a list is accessed by index.
Dictionaries are unordered, while lists are ordered.
Example: dict = {'name': 'John', 'age': 30}, list = ['apple', 'banana', 'cherry']

Asked in Accenture

Q. What are window functions?
Window functions in SQL are used to perform calculations across a set of table rows related to the current row.
Window functions are used to calculate cumulative sums, averages, ranks, and more.
They operate on a set of rows related to the current row, known as the window frame.
Examples include ROW_NUMBER(), RANK(), SUM() OVER(), and AVG() OVER().

Asked in JLL Technologies

Q. outputs of left join, right join & full join
Left join includes all records from the left table and matching records from the right table. Right join includes all records from the right table and matching records from the left table. Full join includes all records when there is a match in either left or right table.
Left join: includes all records from the left table and matching records from the right table
Right join: includes all records from the right table and matching records from the left table
Full join: includes a...read more

Asked in Infosys

Q. What is incremental data loading?
Incremental data loading is the process of adding new data to an existing dataset without reloading all the data.
It involves identifying new data since the last update
Only the new data is added to the existing dataset
Helps in reducing processing time and resource usage
Commonly used in data warehousing and ETL processes

Asked in JLL Technologies

Q. Int & Float data types and their uses
Int & Float data types are used to represent whole numbers and decimal numbers respectively in programming.
Int data type is used for whole numbers without any decimal points, such as 5, -10, 1000
Float data type is used for numbers with decimal points, such as 3.14, -0.5, 10.75
Int data type is typically used for counting or indexing, while Float data type is used for calculations involving fractions or decimals

Asked in DP World

Q. What problems did you solve in your previous organization?
Implemented data pipelines to optimize data processing and analysis.
Developed ETL processes to extract, transform, and load data from various sources.
Designed and implemented data models to support business intelligence and reporting.
Optimized query performance and data storage to improve overall system efficiency.

Asked in RNF Technologies

Q. What is the difference between a left join and a right join?
Left join returns all records from the left table and the matched records from the right table, while right join returns all records from the right table and the matched records from the left table.
Left join keeps all records from the left table, even if there are no matches in the right table.
Right join keeps all records from the right table, even if there are no matches in the left table.
Example: If we have a table of employees and a table of departments, a left join will r...read more

Asked in YouGov

Q. What is a data warehouse?
A data warehouse is a centralized repository that stores structured and unstructured data from various sources for analysis and reporting.
Data warehouses are designed for query and analysis rather than transaction processing.
They typically store historical data and are used for creating reports, dashboards, and data visualizations.
Data warehouses often use ETL (extract, transform, load) processes to integrate data from different sources.
Examples of data warehouse technologies...read more

Asked in Purple

Q. What are SQL commands?
SQL commands are instructions used to interact with databases to perform tasks such as querying, updating, and managing data.
SQL commands are used to perform various operations on databases, such as SELECT, INSERT, UPDATE, DELETE.
Examples of SQL commands include SELECT * FROM table_name, INSERT INTO table_name (column1, column2) VALUES (value1, value2), UPDATE table_name SET column1 = value1 WHERE condition, DELETE FROM table_name WHERE condition.
SQL commands can also be used...read more

Asked in Concentrix Catalyst

Q. Spark performance tuning methods
Spark performance tuning methods involve optimizing resource allocation, data partitioning, and caching.
Optimize resource allocation by adjusting memory and CPU settings in Spark configurations.
Partition data effectively to distribute work evenly across nodes.
Utilize caching to store intermediate results in memory for faster access.
Use broadcast variables for small lookup tables to reduce shuffle operations.
Monitor and analyze Spark job performance using tools like Spark UI a...read more
Asked in VELAN IT Solutions

Q. Joins between tables and syntaxes
Understanding joins between tables and their syntaxes is crucial for data engineers.
Different types of joins include inner join, left join, right join, and full outer join.
Syntax for joining tables typically involves specifying the tables to join, the columns to join on, and any additional conditions.
Example: SELECT * FROM table1 INNER JOIN table2 ON table1.column = table2.column

Asked in Amadeus

Q. What is the Catalyst optimizer?
Catalyst optimizer is a query optimization framework in Apache Spark that improves performance by generating optimized query plans.
Catalyst optimizer is a rule-based optimization framework.
It leverages advanced techniques like predicate pushdown, constant folding, and null propagation.
Catalyst optimizer helps in generating efficient query plans for Spark SQL queries.
It performs optimizations like filter pushdown, projection pruning, and join reordering.
Example: Catalyst optim...read more

Asked in Verificient Technologies

Q. What is TCP/IP?
TCP/IP is a set of communication protocols used for interconnecting network devices on the internet.
TCP (Transmission Control Protocol) ensures reliable data transmission by establishing a connection before data transfer.
IP (Internet Protocol) is responsible for addressing and routing packets of data between devices on a network.
TCP/IP is the foundation of the internet, enabling communication between different devices and networks.
Example: When you access a website, your brow...read more

Asked in AmbitionBox

Q. What is the difference between DELETE and TRUNCATE statements?
Delete removes specific rows from a table, while Truncate removes all rows from a table.
Delete is a DML operation, while Truncate is a DDL operation.
Delete can be rolled back, while Truncate cannot be rolled back.
Delete operation is slower compared to Truncate operation.
Delete operation maintains the integrity constraints, triggers, and indexes, while Truncate does not.

Asked in Optum Global Solutions

Q. Hive Optimization techniques
Hive optimization techniques improve query performance in Hive by optimizing data storage and query execution.
Partitioning tables based on commonly used columns to reduce data scanned during queries
Using bucketing to evenly distribute data across files for faster reads
Using indexes to speed up query processing by creating index tables on frequently queried columns
Optimizing query execution by using appropriate join strategies and tuning query settings

Asked in TCS

Q. Write SQL queries.
I have experience writing SQL queries for data manipulation and analysis.
Use SELECT statement to retrieve data from a database
Use WHERE clause to filter results based on specific conditions
Use JOIN clause to combine data from multiple tables
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