A Data Warehouse Developer is a professional who plays a crucial role in designing, developing, and maintaining data warehouses within an organization. Data warehouses are repositories that store large volumes of data collected from various sources, enabling businesses to analyze and gain insights from their data effectively. In this blog post, we will describe the primary responsibilities and the most in-demand hard and soft skills for Data Warehouse Developers.

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Main Responsibilities of a Data Warehouse Developer

The following list describes the typical responsibilities of a Data Warehouse Developer:

Analyze

Analyze and understand complex databases and AGF's systems of data.

Assist in

• Assist and lead movement from an on premise environment to Azure Cloud – end to end experience.

• Assist in designing and implementing data visualization and reporting tools.

• Assist less experienced peers by providing technical guidance.

• Assist subordinates with debugging whenever necessary.

• Assist the Test Team on the testing of deliverables.

Automate

Automate data warehouse processes and workflows to improve efficiency.

Build

Build algorithms and prototypes.

Carry out

Carry out continual reviews and maintenance of the Data Warehouse documentation.

Coach

Coach and assist other colleagues.

Collaborate with

• Collaborate with business analysts and stakeholders to gather data requirements and define data models.

• Collaborate with business stakeholders to understand their reporting and analytics requirements.

• Collaborate with cross-functional teams to define and implement data governance policies.

• Collaborate with data architects to ensure data warehouse scalability and flexibility.

• Collaborate with database administrators to ensure availability and reliability of the data warehouse.

• Collaborate with data scientists and analysts to develop data models and algorithms.

• Collaborate with other teams and departments to ensure excellent levels of client service.

• Collaborate with the team to build efficient processes for data visualizations with Tableau software.

Conduct

• Conduct and participate in code walk-throughs and document technical design.

• Conduct data performance testing and tuning for optimal query execution.

• Conduct data profiling and quality assessments to identify and rectify data anomalies.

• Conduct highly complex work critical to the organization.

• Conduct performance tuning and capacity planning for scalability of the data warehouse.

• Conduct root cause analysis for data-related incidents and propose preventive measures.

• Conduct unit and system tests.

• Conduct user training and workshops to promote data literacy within the organization.

Contribute

Contribute and interact with Azure DevOps ecosystem, e.g. Wiki, Boards, Epics, Stories and Features.

Convert

Convert business requirements to technical specifications.

Create

• Create and maintain documentation for data warehouse processes, data flows, and data mappings.

• Create and maintain testable, maintainable data pipelines in python.

• Create and maintain the databases required for development, testing and production.

• Create dashboards and reports using OBIEE and other tools as required.

• Create documentation required by IAS such as release notes and Interface Control Documents.

• Create new and extend existing operational documentation.

• Create project documentation according to the Project Management Office Standards. . &#.

• Create technical spec plans and documents, etc..

Design

• Design and build new data products to meet business needs.

• Design and deploy data table structures, reports and queries, etc..

• Design and implement Microsoft Azure services, including APIs, Event Hub, and Cosmos DB.

• Design data warehouse structures to support efficient data storage and retrieval.

Develop

• Develop analysis and design of transactional systems and / or programs.

• Develop and execute database queries and conduct analyses.

• Develop and maintain data extraction and reporting processes for business intelligence purposes.

• Develop and maintain internal data warehouse and reporting systems.

• Develop a quality assurance / quality control process for maintaining high-quality data.

• Develop common operations, which can be reused.

• Develop complete descriptions of all specifications and solutions required.

• Develop data integration and ETL / ELT solutions between our various databases and business systems.

• Develop data integration and ETL solutions between our various databases and business systems.

• Develop ETL (Extract, Transform, Load) processes for data extraction and loading.

• Develop queries and reports to support our reporting applications like Seismic and MicroStrategy.

Document

Document procedures, processes and standards (e.g. data dictionary) for the data warehouse.

Engage

Engage subject matter experts and other team members to work thru challenges.

Ensure

• Ensure data is reliably stored and secured.

• Ensure security of all data.

• Ensure that all organizational data is managed according to privacy FOIP and HIA requirements.

Establish

Establish the needs of users and monitoring user access and security.

Foster

Foster positive team engagement.

Help

• Help and assist you SAS ETL Developers with more complex ETL objects.

• Help devise and layout a high-quality infrastructure, upon which future data science can flourish.

• Help up skill other analytical team members into advanced data science techniques.

Identify

Identify opportunities for data acquisition.

Implement

• Implement data archiving and data lifecycle management strategies.

• Implement data governance policies and procedures to ensure data integrity and compliance.

• Implement data integration and data cleansing processes to ensure data accuracy and consistency.

• Implement security measures to protect sensitive data within the data warehouse.

Interpret

Interpret test results.

Keep

Keep abreast of external / industry best practices and brings back learnings to the team.

Learn

Learn user functions, organization and role in the enterprise to the extent required.

Maintain

Maintain and enhance existing data and reporting datasets to maximize business impact.

Manage

Manage and prioritise workloads to deliver at agreed milestones.

Mentor

Mentor junior team members within the team and across Duo.

Monitor

Monitor and maintain the health and stability of the data warehouse environment.

Optimize

Optimize data warehouse performance through SQL query fine-tuning, index optimization, and partitioning.

Participate

• Participate in data warehouse performance optimization projects.

• Participate in evaluating and selecting data warehousing tools and technologies.

• Participate in integrated projects / Best BI Solutions - PowerBI, etc..

Perform

• Perform all other duties as assigned.

• Perform all other related duties as assigned.

• Perform data analysis to identify trends, patterns, and insights within the data warehouse.

• Perform or assist in data integration design and documentation.

• Perform system integration as well as support work for current systems.

• Perform tasks and processes and uses a range of technical tools to carry out job duties.

• Perform unit and system testing to ensure the changes are defect free.

• Perform Unit Tests, track defects and implement solutions.

Prepare

Prepare data for prescriptive and predictive modelling.

Provide

• Provide accurate time estimates for work to be undertaken.

• Provide ad-hoc reporting support and guidance to the Business Departments as required.

• Provide early life support for new releases and a Flexible Analytics Capability.

• Provide estimates of timescales for the work on behalf of the UK MIS Team.

• Provide technical guidance and support to team members and stakeholders.

Research

Research, document, and share knowledge with the project team.

Scope

Scope and define work effort through estimates.

Seek

Seek continuous improvement in performance & tuning of data warehouse and ensure security of data.

Solve

Solve unique and complex problems with broad impact on the business.

Stay up-to-date with

Stay up-to-date with industry trends and advancements in data warehousing technologies.

Support

Support the performance of the data warehouse systems.

Take

Take a leadership role in owning quality.

Troubleshoot

• Troubleshoot and resolve data integration and migration issues.

• Troubleshoot and resolve data-related issues reported by users or system alerts.

• Troubleshoot and solve technical problems.

• Troubleshoot issues with database views and query performance.

• Troubleshoot issues with database views and query performance, and reports.

Understand

• Understand difference between SCD1 and SCD2.

• Understand, utilize and communicate best practice methodologies and industry standards.

Work with

• Work and collaborates with other business partner.

• Work closely with key business data and designs solutions.

• Work closely with the business analyst(s), and other team members, to understand requirements.

• Work on other project tasks as assigned.

• Work with minimal supervision.

• Work with moderate supervision with latitude for independent judgment.

Most In-demand Hard Skills

The following list describes the most required technical skills of a Data Warehouse Developer:

1. SQL (Structured Query Language) proficiency for data manipulation and querying.

2. Expertise in ETL (Extract, Transform, Load) processes and tools.

3. Data modeling and database design skills.

4. Knowledge of data warehousing concepts and architectures.

5. Proficiency in data integration and data cleansing techniques.

6. Familiarity with data profiling and data quality assessment tools.

7. Experience with data visualization and reporting tools (e.g., Tableau, Power BI).

8. Strong understanding of relational databases and dimensional modeling.

9. Knowledge of data governance and data management best practices.

10. Familiarity with programming languages like Python or Java for scripting and automation.

11. Experience with data migration and data archiving techniques.

12. Expertise in performance tuning and query optimization.

13. Familiarity with cloud-based data warehousing platforms (e.g., Amazon Redshift, Google BigQuery).

14. Knowledge ofdata security and privacy practices for protecting sensitive data.

15. Proficiency in data analysis and data mining techniques.

16. Experience with data warehouse automation tools and frameworks.

17. Knowledge of distributed computing and parallel processing for large-scale data processing.

18. Familiarity with data virtualization and data federation technologies.

19. Understanding of data governance frameworks and regulations (e.g., GDPR, CCPA).

20. Proficiency in data profiling and metadata management tools.

Most In-demand Soft Skills

The following list describes the most required soft skills of a Data Warehouse Developer:

1. Strong analytical and problem-solving skills.

2. Excellent communication and interpersonal skills for collaborating with cross-functional teams.

3. Ability to work effectively in a team environment.

4. Detail-oriented mindset for ensuring data accuracy and quality.

5. Strong organizational and time management skills.

6. Adaptability and flexibility to work in a dynamic and evolving data environment.

7. Critical thinking and decision-making skills for resolving data-related issues.

8. Continuous learning mindset to keep up with emerging data warehousing technologies.

9. Strong documentation and presentation skills.

10. Ability to translate technical concepts into non-technical terms for stakeholders.

Conclusion

A Data Warehouse Developer plays a critical role in the design, development, and maintenance of data warehouses. Their responsibilities range from designing data structures to optimizing performance, ensuring data integrity, and supporting data analysis. To excel in this role, Data Warehouse Developers require a combination of hard skills such as SQL proficiency, data modeling, ETL processes, and data integration, as well as soft skills like analytical thinking, communication, and problem-solving abilities. By possessing these skills, Data Warehouse Developers contribute to the successful implementation and utilization of data warehousing solutions within organizations.