Data Warehouse Engineer

The Data Warehouse Engineer is tasked with overseeing the full life-cycle of back-end development of the business’s data warehouse. The Data Warehouse Engineer is responsible for the development of ETL processes, cube development for database and performance administration, and dimensional design of the table structure.

The Data Warehouse Engineer works closely with the data analysts, data scientists, product management, and senior data engineering teams in order to power insight and avail meaningful data products for the business and enable consistently informed management decisions.

Objectives and Responsibilities of the Data Warehouse Engineer

Management: The Data Warehouse Engineer plays a managerial role where he provides day-to-day support of the data warehouse and troubleshoots existing procedures and process. He defines and promotes the department’s best practices and design principles for data warehousing techniques and architecture. The Data Warehouse Engineer additionally strives to improve data organization and accuracy. In this capacity, he monitors and troubleshoots performance issues on data warehouse servers and assists in the development of business intelligence, business data standards, and processes.

The Data Engineer also plays a key role in technological decision making for the business’s future data, analysis, and reporting needs. He supports the business’s daily operations inclusive of troubleshooting of the business’s data intelligence warehouse environment and job monitoring. It is also the role of the Data Warehouse Engineer to guide the business in identifying any new data needs and deliver mechanisms for acquiring and reporting such information as well as addressing the actual needs.

Design/Strategy: The Data Warehouse Engineer designs and supports the business’s database and table schemas for new and existent data sources for the data warehouse. He additionally creates and supports the ETL in order to facilitate the accommodation of data into the warehouse using SSIS and other technologies. In this capacity, the Data Warehouse Engineer designs and develops systems for the maintenance of the business’s data warehouse, ETL processes, and business intelligence.

Collaboration: The role that the Data Warehouse Engineer plays is highly collaborative and, as such, he works closely with data analysts, data scientists, and other data consumers within the business in an attempt to gather and populate data warehouse table structure, which is optimized for reporting. The Data Warehouse Engineer also works closely with other disciplines/departments and teams across the business in coming up with simple, functional, and elegant solutions that balance data needs across the business.

The Data Warehouse Engineer partners with the senior data analytics management and senior data warehouse engineering in an attempt to refine the business’s data requirements, which must be met for building and maintaining data warehouses.

Analytics: The Data Warehouse Engineer plays an analytical role in quickly and thoroughly analyzing business requirements for reporting and analysis and subsequently translating the emanating results into good technical data designs. In this capacity, the Data Warehouse Engineer establishes the documentation of reports, develops, and maintains technical specification documentation for all reports and processes.

Knowledge: The Data Warehouse Engineer is also tasked with gathering and maintaining best practices that can be adopted in big data stacking and sharing across the business. The Data Warehouse Engineer provides expertise to the business in the areas of data analysis, reporting, data warehousing, and business intelligence. It is also the Data Warehouse Engineer’s duty to provide technical expertise to the business on business intelligence data architecture and also on structured approaches for transitioning manual applications and reports to the business.

Other Duties: The Data Warehouse Engineer plays similar duties as he deems fit for the proper execution of his duties and duties as delegated by the Senior Data Warehouse Engineer, Head of Analytics, Director Analytics, Chief Data Officer, or the Employer.

Required Qualifications of the Data Warehouse Engineer

Education: The Data Warehouse Engineer has to have a bachelor’s degree in Computer Science, Data Science, Information Technology, Information Systems, Statistics, or any other related field. An equivalent of the same in working experience is also acceptable for the position.

Experience: A candidate for this position has to have experience of at least 2 years in SQL server coding and SQL server database administration. The candidate has to have additional experience working with SQL server integration services or any similar ETL tools. The candidate must also demonstrate a strong understanding of dimensional modeling as well as other data warehousing techniques.

A suitable candidate for this position will also have had experience in data warehouse development and architecture and hands-on physical and logical database designing. The candidate will additionally have experience with Teradata, coupled with experience working on projects within a collaborative setting composed of cross-functional, technical, and non-technical personnel. The candidate will further have had experience working with Tableau or any other business analytics platforms, for example, SpagoBI.

Communication Skills: Communication skills are a must have for the Data Warehouse Engineer. These skills will be necessary in facilitating the clear conveyance of technical communications in cross-functional settings. Communication skills will also be necessary in the drafting of clear and understandable data designs that will be reviewed by senior data warehouse engineers as well as the clear articulation of documentation and reporting processes that will apply across the business. The adherence to these processes and their maintenance will be highly dependent on the clarity with which they are described and conveyed by the Data Warehouse Engineer.

Computer Skills/Ms Office/Software: The Data Warehouse Engineer must possess excellent computer skills and be highly proficient in the use of Ms Word, PowerPoint, Ms Excel, MS Project, MS Visio, and MS Team Foundation Server, which will all be necessary in the creation of visually and verbally engaging data designs and tables as well as the communication of documentation and reporting processes for use across all departments in the business. The candidate’s proficiency in data visualization tools will also make him better suited to play this role.

Analytics: A candidate for this position must have a deep passion for data analytics technologies as well as analytical and dimensional modeling. The candidate must be extensively familiar with ETL (Extraction, Transformation & Load), data warehousing, and business intelligence tools such as Qlikview. The candidate must have the skill to draft, analyze, and debug SQL queries and also be proficient in a scripting language, for example, Java, Python, C Sharp, Perl, R, and so forth. The candidate must also have vast knowledge of database design and modeling in the context of data warehousing. He will additionally be skilled in diagnosing complex data warehouse ETL processes, business logic failures, and data flows, in order to quickly resolve issues.

Interpersonal Skills: The Data Warehouse Engineer has to be an individual with a positive can-do attitude, be open and welcoming to change, be a self-starter and be self-motivated, have an insatiable thirst for knowledge, be proactive and go beyond the call of duty, take accountability for business performance, have innovative problem solving skills, be a creative and strategic thinker, and have an ability to remain calm and composed in times of stress and uncertainty.

People Skills: The Data Warehouse Engineer must have an ability to establish strong, meaningful, and lasting relationships with others. He will be approachable and likable inspiring trust and a feeling of dependability in others, hence, giving more credibility to his insights and directives in the view of collaborating personnel, senior management, and his colleagues.

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