Data Warehouse Engineer Job Description – Career Deep Dive

A Data Warehouse Engineeer is a highly skilled professional responsible for designing, implementing, and maintaining data warehouses. They play a critical role in ensuring that organizations have access to accurate and timely data, which is essential for making informed business decisions. In this blog post, we’ll explore the key responsibilities of a Data Warehouse Engineer, what a typical day in the role looks like, the qualifications required, and sample interview questions.

Data Warehouse Engineer Job Description

As a Data Warehouse Engineer, you will be responsible for designing and maintaining the organization’s data warehouse, developing ETL workflows using tools such as Python or Java, writing complex SQL queries to extract and transform data from source systems, and designing and maintaining data models using tools such as ER/Studio or Visio. You will work closely with the business intelligence team to ensure that the data warehouse meets business requirements and supports the organization’s goals, troubleshoot and resolve data warehouse issues, and optimize data warehouse performance. The ideal candidate will have a strong understanding of data warehousing concepts, SQL, ETL tools, and data modeling, as well as excellent problem-solving and communication skills.

Key Responsibilities for a Data Warehouse Engineer

As a Data Warehouse Engineer, your primary responsibility is to design, build, and maintain data warehouses. This involves working closely with stakeholders to understand their requirements, designing data models and ETL (Extract, Transform, Load) processes, and ensuring that the data warehouse is optimized for performance and scalability. Other key responsibilities include:

• Developing and implementing data governance policies and procedures
• Troubleshooting and resolving issues related to data quality and performance
• Collaborating with other data professionals, such as Business Intelligence Analysts and Data Scientists, to ensure that data is available and accessible
• Staying up-to-date with the latest technologies and trends in data warehousing to ensure that the organization remains competitive

What does a Normal Day Look Like?

A typical day for a Data Warehouse Engineer is highly varied and involves a mix of technical and non-technical tasks. On any given day, you may be:

• Meeting with stakeholders to understand their data requirements
• Designing and building ETL processes to extract, transform, and load data into the data warehouse
• Troubleshooting and resolving issues related to data quality and performance
• Collaborating with other data professionals to ensure that data is accessible and accurate
• Researching and staying up-to-date with the latest technologies and trends in data warehousing

How Much does a Data Warehouse Engineer make in 2023?

According to Glassdoor, Data Warehouse Engineers typically make $122,656 total pay per year with a normal range anywhere between $97k and $157k.

The highest reported Data Warehouse Engineer on Glassdoor makes $195k per year.

Typical Tools and Languages

Data Warehouse Engineers work with a variety of tools and languages to design, build, and maintain data warehouses. Here are some of the most common tools and languages that Data Warehouse Engineers use:

• SQL: Structured Query Language (SQL) is the most common language used for managing and manipulating data in a data warehouse. Data Warehouse Engineers must have a strong understanding of SQL and be able to write complex queries to extract and transform data.
• ETL Tools: Extract, Transform, and Load (ETL) tools are software applications that are used to automate the process of moving data from source systems to a data warehouse. Some popular ETL tools include Informatica, Talend, and Microsoft SSIS.
• Data Modeling Tools: Data modeling tools are used to design the data schema for a data warehouse. These tools allow Data Warehouse Engineers to create entity-relationship diagrams (ERDs) that define the structure of the data warehouse. Some popular data modeling tools include ER/Studio, IBM InfoSphere Data Architect, and Microsoft Visio.
• Data Visualization Tools: Data Visualization tools are used to create reports and dashboards that make it easy for business users to analyze and interpret data. Some popular data visualization tools include Tableau, Power BI, and QlikView.
• Cloud Platforms: Cloud platforms such as AWS, Azure, and Google Cloud Platform provide a scalable and cost-effective way to build and maintain data warehouses. Data Warehouse Engineers must have a strong understanding of cloud technologies and be able to design and deploy data warehouses in the cloud.

We’ve done the work reviewing and ranking the best data engineering tools in a separate post which is a good starting point.

In addition to these tools and languages, Data Warehouse Engineers must also be familiar with other technologies such as data governance tools, version control tools, and programming languages such as Python and Java. Keeping up-to-date with the latest technologies and trends in data warehousing is essential for Data Warehouse Engineers to remain competitive in the job market.

Qualifications

To become a Data Warehouse Engineer, you’ll typically need a degree in computer science, software engineering, or a related field. You’ll also need to have a strong understanding of databases, data modeling, ETL processes, and data warehousing concepts. Other key qualifications include:

• Strong problem-solving and analytical skills
• Excellent communication and collaboration skills
• Experience with data warehousing tools and technologies such as SQL, ETL tools, and data visualization tools
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform
• Familiarity with Agile methodologies and DevOps practices

A great way to show competence with different technologies and languages is to obtain certificates online from different vendors. It’s very common in the industry and often looked upon favourably in job applications. We’ve compiled a list of the best certificates available in this post.

Sample Interview Questions for a Data Warehouse Engineer

Here are some sample interview questions that you may be asked when interviewing for a Data Warehouse Engineer role:

• What experience do you have with designing and building data warehouses?
• How do you ensure that your data warehouse is optimized for performance and scalability?
• Can you walk me through a recent project where you had to troubleshoot and resolve issues related to data quality or performance?
• How do you stay up-to-date with the latest technologies and trends in data warehousing?
• What experience do you have with cloud platforms such as AWS or Azure?
• How do you approach data governance and ensuring data accuracy and security in your data warehouse?
• Can you walk me through a recent project where you had to collaborate with other data professionals such as Business Intelligence Analysts or Data Scientists?

Data Warehouse Engineers play a critical role in ensuring that organizations have access to accurate and timely data, which is essential for making informed business decisions. To become a Data Warehouse Engineer, you’ll need to have a strong understanding of databases, data modeling, ETL processes, and data warehousing concepts. You’ll also need to have excellent problem-solving and communication skills, as well as experience with data warehousing tools and technologies.

Ben

Ben is a full-time data leadership professional and a part-time blogger.

When he’s not writing articles for Data Driven Daily, Ben is a Head of Data Strategy at a large financial institution.

He has over 12 years’ experience in Banking and Financial Services, during which he has led large data engineering and business intelligence teams, managed cloud migration programs, and spearheaded regulatory change initiatives.