The Moat Data Engineer interview guide, interview questions, salary data, and interview experiences.

Moat Data Engineer Interview Guide

Getting ready for an Data Engineer interview at Moat? The Moat Data Engineer interview span across 10 to 12 different question topics. In preparing for the interview:
<ul>
<li>Know what skills are necessary for Moat Data Engineer roles.</li>
<li>Gain insights into the Data Engineer interview process at Moat.</li>
<li>Practice real Moat Data Engineer interview questions.</li>
</ul>
Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the Moat Data Engineer interview.


Getting ready for an Data Engineer interview at Moat? The Moat Data Engineer interview span across 10 to 12 different question topics. In preparing for the interview:

- Know what skills are necessary for Moat Data Engineer roles.
- Gain insights into the Data Engineer interview process at Moat.
- Practice real Moat Data Engineer interview questions.

Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the Moat Data Engineer interview.
        

Overview

Moat Data Engineer Salary

We've gathered this data from parsing thousands of interview experiences sourced from members.

We've gathered this data from parsing thousands of interview experiences sourced from members.

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

Moat Data Engineer Interview Process

Given a table called <code>employees</code>, get the largest salary of any employee by department

Example:

Input:

<code>employees</code> table

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

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

<tr>
<td><code>department</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>salary</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>
Output:

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

<tbody>
<tr>
<td><code>department</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>largest_salary</code></td>
<td>INTEGER</td>
</tr>
</tbody>
</table>

Write a query to get the largest salary of any employee by department

Largest Salary by Department

You’re tasked with designing a database system for Swipe Inc., a company that manages payments for software developers. Swipe manages a set of APIs so developers can abstract payment processes for their web service and transfer control over to Swipe’s APIs to manage payment security and finance handling (contacting credit card providers, etc.)

Your database system should store a collection of API keys with their attributes, as shown in the example below:

<pre tabindex="0" class="chroma"><code>{
 &#34;API_key&#34;:{
 &#34;Transaction_list&#34;:{
 &#34;User_ID&#34;:{
 &#34;Name&#34;:{
 &#34;f_name&#34;: 
 &#34;l_name&#34;: 
 }
 &#34;Card_Details&#34;:{
 &#34;Bank&#34;:
 &#34;Card_No&#34;:
 &#34;Expiry&#34;:
 &#34;CV&#34;:
 } 
 }
 }
 &#34;Curr_balance&#34;:
 }
}
</code></pre>

What are the functional and non-functional requirements for this database?

Determine the requirements for designing a database system to store payment APIs

Swipe Payment API

You are given a dictionary with a key-value of <code>{string: number}</code> where values in the dictionary could be duplicates. You are required to extract the unique values from the dictionary where the value occurred only once.

Return a list of values where they occur only once.

Note: You can return the values in any order.

Input:

<pre tabindex="0" class="chroma"><code>dictionary = {&#34;key1&#34;: 1, &#34;key2&#34;: 1, &#34;key3&#34;: 7, &#34;key4&#34;: 3, &#34;key5&#34;: 4, &#34;key6&#34;: 7}
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>find_unique_values(dictionary) -&gt; [3,4]

#Only 3 and 4 occurred once.
</code></pre>

Dictionary Unique Values

Moat Data Engineer Interview Questions

Castleton Commodities International, a leading global energy commodities merchant and investor, seeks a Data Engineer. This crucial role involves integrating new data management platforms, constructing data ingestion pipelines, and collaborating with global Risk and commercial investing teams. The successful candidate will contribute significantly to the firm's investment platform, supporting its mission to generate strong risk-adjusted returns through proprietary capital deployment.
In this role you can expect to have the responsibilities:

Execute data architecture and management projects for new and existing data sources
Transition data sets, databases, and code to a new technology stack
Lead data set analysis using techniques including machine learning
Manage data ingestion process and publishing to investment teams
Map, standardize, and normalize data
Conduct research on vendor trends and best practices
Create workflows to manage data loads and perform quality analysis
Manage vendor relationships and data input changes
Prioritize and resolve data issues based on business usage
Assist with big data projects for the commercial business
Partner with commercial teams to understand data flow and gather requirements
Identify and remediate gaps in current datasets
This role comes with the following benefits:

Comprehensive medical, dental, retirement, and life insurance
Employee assistance & wellness programs
Parental and family leave policies
Volunteering opportunities through charity committees
Charitable contribution match program
Tuition assistance & reimbursement
Quarterly Innovation & Collaboration Awards
Employee discount program including fitness facilities
Competitive paid time off
Continued learning opportunities
This role requires you to have:

Bachelor’s degree in Computer Science, Mathematics, Physics, Business Intelligence, or related field
5+ years in SQL programming, data architecture, and dimension modeling
Passion for data architecture, analytics, management, and programming
Experience in energy commodities or financial services
Experience in mapping, standardizing, and normalizing data
Experience with data integration platforms, SnapLogic preferred
Experience with ETL/ELT frameworks
Advanced skills in writing optimized SQL code
Experience with Snowflake or Oracle
Python experience with Pandas, Numpy, and Scikit
Ability to communicate with technical and non-technical users
Team player with the ability to manage changing projects and priorities
Strong analytical skills with attention to detail
You would benefit from having:

Familiarity with Power BI and Tableau
Interest or experience in machine learning/Artificial Intelligence

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We are seeking a skilled Data Engineer to join the Data team at our client in the Insurance industry. This role is crucial to driving the success of the Data Strategy, ensuring that their data infrastructure is robust, reliable, and scalable to support company's rapid growth and commitment to excellence. As a Data Engineer, you will maintain and update the data pipelines and data warehouse, supporting Insight and Analytics with table creation, business logic, and stakeholder management. Working closely with the Head of Data, you will play a crucial role in enhancing data quality and building trust in the data platform, ensuring company’s data infrastructure is future ready. Key Responsibilities <ul><li>Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines within Microsoft Fabric using tools like Azure Data Factory, Dataflows, Power Query, and Synapse Pipelines. </li><li>Data Modelling: Create high performance data models in Synapse and Power BI for effective reporting and analytics. </li><li>Data Integration: Consolidate diverse data sources into a unified data platform, applying Lakehouse architecture principles. </li><li>Data Transformation: Develop complex data transformations using SQL, PySpark, and other tools within Microsoft Fabric. </li><li>Collaboration: Partner with data analysts and business stakeholders to deliver technical solutions aligned with data requirements. </li><li>Performance Optimisation: Monitor and optimize data pipelines, queries, and storage layers for performance and cost efficiency. </li><li>Security and Compliance: Implement best practices for data security and ensure compliance with policies and regulations such as GDPR and HIPAA. </li></ul> Experience and Qualifications <ul><li>Proficiency in Azure Data Factory, Power Query, Dataflows, and Synapse Pipelines. </li><li>Advanced understanding of data warehousing (e.g., star schema) and experience with data model design in Synapse and Power BI. </li><li>Skilled in SQL, Python, and PySpark for data transformation and querying. </li><li>Extensive ETL/ELT experience, including batch and streaming processes in Fabric tools. </li><li>Proven ability to optimise data pipelines, ETL jobs, and queries for efficiency and cost effectiveness. </li><li>Preferred knowledge of Azure Data Lake, Azure SQL Database, Synapse SQL pools, and Delta Lake. </li><li>Industry experience in insurance, particularly broking (preferred). </li><li>Bachelor's or master's degree in computer science, Information Technology, or a related field (preferred). </li></ul> This is a full-time role UK based with occasional travel to the London office.

The Detroit Tigers, a part of Major League Baseball (MLB), are seeking a Cloud Data Engineer for their Baseball Systems. This role focuses on the design, management, and automation of data processes to enhance Baseball Operations. The candidate will work closely with the Director of Baseball Systems.
In this role you can expect to have the responsibilities:

Design, implement, and maintain data architecture and processing pipelines at scale.
Develop and use data quality assurance frameworks to identify inconsistent data patterns.
Collaborate with Tigers data engineers and data scientists to implement good data hygiene practices.
Work with external data vendors to address data quality issues.
Automate and execute test cases in data pipelines and manage data issue tracking.
This role comes with the following benefits:

Equal Employment Opportunity employer
This role requires you to have:

2+ years in data engineering using SQL and Python.
Familiarity with cloud computing and services, preferably Azure.
Experience with cloud-based data lakes and data warehouses.
Proficiency with Apache Spark, ideally on Azure Databricks.
Knowledge of continuous integration, regression testing, and versioning strategies.
Experience with SQL data warehouses for data science and analytics.
Understanding of data quality frameworks and best practices.
Familiarity with baseball and current baseball research.
You would benefit from having:

Familiarity with Airflow.
Effective communication skills for explaining technical concepts.
SQL administrative skills (T-SQL preferred).
Experience with generating reports and visuals on large data sources.
Experience with DevOps practices for CI/CD pipelines.
Experience with containers and container deployment.
Familiarity with open-source data quality frameworks (Great Expectations preferred).
The position may require evening, weekend, and holiday hours. The Detroit Tigers are committed to providing reasonable accommodations for applications during the hiring process.

#J-18808-Ljbffr

Moat Data Engineer Interview Guide

Overview

Moat Data Engineer Salary

Moat Data Engineer Interview Process

Moat Data Engineer Interview Questions

Moat Data Engineer Jobs