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Let’s say we have a table with an <code>id</code> and <code>name</code> fields. The table holds over 100 million rows and we want to sample a random row in the table without throttling the database.

Write a query to randomly sample a row from this table.

Input:

<code>big_table</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a query to randomly sample a row from a big table.

Random SQL Sample

Let’s say that your company is running a standard control and variant AB test on a feature to increase conversion rates on the landing page. The PM checks the results and finds a .04 p-value.

How would you assess the validity of the result?

Experiment Validity

Let’s say you work for a social media company that has just done a launch in a new city. Looking at weekly metrics, you see a slow decrease in the average number of comments per user from January to March in this city.

The company has been consistently growing new users in the city from January to March.

What are some reasons why the average number of comments per user would be decreasing and what metrics would you look into?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

Decreasing Comments

How would you investigate a decline in the average number of comments per user?

National Australia Bank Salaries by Position

PFB JD for Data Engineer - Essential capabilitiesAdvanced or demonstrable experience in SQL, Python,Experience with Source code control (GitHub) and JenkinsAbility to design, develop, execute, complete ETLAbility to articulate complex technical issues and desired outcomes of system enhancements<ul><li>Proven analytical skills and evidence-based decision making</li><li>Excellent problem solving, troubleshooting & documentation skills</li><li>Strong written and verbal communication skills</li><li>Excellent collaboration and interpersonal skills</li><li>Strong delivery focus with an active approach to quality and auditability</li></ul> Desired Capabilities<ul><li>Experience with Artifactory and Jenkins for deployment of Production code</li><li>Knowledge and exposure to Big Data technologies Hadoop stack such as HDFS, Hive, Impala, Spark etc, and cloud Big Data warehouses - RedShift, DataBricks.</li><li>Exposure to AWS technologies including EMR, Glue, Athena, Data Pipeline, Lambda</li><li>Exposure to technologies such as Airflow, GSC, GitHub</li></ul> ExperienceHands on in SQL and its Big Data variants (Hive-QL, DataBricks ANSI, Redshift SQL)It is expected that the role holder will most likely have the following qualifications and experience<ul><li>4+ years technical experience (within financial services industry preferred)</li><li>Solid experience, knowledge and skills in Data Engineering, BI/software development such as ELT/ETL, data extraction and manipulation in Data Lake/Data Warehouse/Lake House environment.</li><li>Hands on programming experience in writing Python, SQL, Unix Shell scripts, Pyspark scripts, in a complex enterprise environment</li><li>Experience in configuration management using Ansible/Jenkins/GIT</li><li>Hands on experience of using AWS Services - S3,EC2, EMR, SNS, SQS, Lambda functions, Redshift</li><li>Experience with Source Control Tools Github or BitBucket</li><li>Skilled in querying data from a range of data sources that store structured and unstructured data Knowledge or understanding of Power BI (Recommended )</li></ul>

National Australia Bank Interview Questions

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National Australia Bank Interview Questions

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