Data Warehousing Developers

Recruit Developers for Data Warehousing

Over the past decade, there has been an immense growth in the fields of big data and data science. With businesses and organisations recognising the immense potential of data, it has become a crucial factor in making important decisions. With approximately 2.5 quintillion bytes of data produced every day through various means, it has become increasingly challenging to manage such an exponentially increasing data load. This has made it important to seek the assistance of professionals to tackle data processing. This is why organisations, corporations, and firms are seeking the expertise of data warehousing specialists to ensure their data is organised efficiently. Understanding what data warehousing entails is crucial in this regard.

What Exactly Does the Term “Data Warehouse” Mean?

Companies and businesses use data warehousing to gather and store data in secure electronic formats, helping them derive meaningful business insights. This data is sourced from a range of disparate sources and can later be retrieved, analysed and used to improve the business by data analysts and developers. Such information forms the basis of the business intelligence system, which facilitates accurate data analysis and reporting.

The concept of data warehousing started to emerge in the 1980s as businesses faced increasing volumes of data that needed to be collected and managed using technology. Relying solely on transaction processing was no longer sufficient, and so data query and analysis became indispensable. To effectively manage data loads, design and implement data models, organisations are required to hire data warehousing developers.

Data Warehouse Classifications

By analysing data from a data warehouse, businesses can gain deeper insights into their customers. Data warehousing can be categorised into three different levels, based on the level of support and understanding the warehouse data provides.

  • Enterprise data warehouses (EDWs) are data warehouses that provide decision support across an entire organisation. The data in EDWs is systematically organised, presented and analysed to extract valuable insights which inform and guide business decisions, enabling organisations to make more informed and effective choices.
  • The Operational Data Store (ODS) is a dynamic data storage type that is frequently updated in real-time. It is used for mundane tasks such as employee record maintenance, and is an important component relied upon by businesses.
  • Data marts are specialised data warehouses designed to cater to the specific needs of industries such as banking, retail, and logistics. By dividing the collection and analysis of data into separate divisions, companies can better focus on achieving their desired results and make the most efficient use of their data. With data marts, companies can achieve a more focused approach to data analysis, leading to greater accuracy and efficiency.

Data Warehouse Developer Responsibilities

Companies looking to recruit skilled Data Warehouse Developers must ensure that qualified candidates have extensive expertise in data structures, data modelling, programming, business intelligence (BI), SQL, analysis and reporting. The role of Data Warehouse Developers involves managing and distributing data for analysis, among other responsibilities such as:

  • Developing and enhancing data models
  • Monitoring data and adjusting data loads as needed
  • Explain the structures and processes used in the ETL (Extract, Transform and Load) process.
  • Assist in gathering information by supporting various phases of the SDLC (Software Development Life Cycle).
  • Ensuring results are accurate and useful for generating insights
  • Develop code that is efficient and well-implemented to obtain useful information.
  • Monitor activities within the data warehouse and manage the necessary designs for various data functional standards.
  • Verify the quality of the code to ensure that the project can deliver on its promises.

Approaches for the Development of Future Technologies

To perform their duties effectively, Data Warehouse Developers must possess a combination of analytical, technical, and communication skills. They need to have a strong understanding of data analysis, business intelligence, and structured query language to efficiently gather, store, and analyse data. In addition, they should have expertise in designing data models, developing extraction algorithms, and conducting independent problem analysis. Employers looking to ensure a precise and accurate data warehousing operation should seek out candidates who possess the following technical abilities:

  1. Proficiency with ETL (Extract, Transform and Load) Tools

    • Acquiring the ability to produce technical documents that offer the information and details needed to carry out business operations is a crucial skill for Data Warehouse Engineers to have.
    • They should be accustomed to generating multiple POCs (Proof of Concept) to verify the validity of the ETL solution.
    • As per the functional requirements of the business, the developer may need to make modifications to the provided ETL.
    • They must be capable of producing documentation for the entire ETL process.
    • They should possess the ability to enhance the functionality of T-SQL scripts and competently implement and refine documentation.
    • Proficiency in both SQL Server and Oracle (and the ability to implement SSIS, Oracle scheduler, SSRS) is necessary for the developer to effectively carry out ETL processing for the data warehouse.
  2. Hadoop:

    Apache Hadoop is an open-source platform that effectively handles large-scale data collections through distributed computing across multiple computers. It is an excellent solution for processing vast datasets in cost-sensitive environments where applications are hosted on inexpensive servers. For developers, the following details are particularly valuable:
    • Planning and creating applications to integrate both structured and unstructured data in a Hadoop environment.
    • Transforming technical and operational requirements into a program that can function on Hadoop MapReduce or Apache Spark is a significant endeavor.
    • Approaches to maintain the integrity of individual components of a system while migrating to Hadoop-based architectures.
  3. Realizing Data Warehouse Concepts

    Developers who work with data warehouses should have knowledge of the following topics-
    • Installation, development, and maintenance of business intelligence products, data warehousing techniques, and report generation applications.
    • Identification of Key Performance Indicators (KPIs) and tools required for strategic and operational planning.
    • Approaches for designing and developing software to verify the accuracy of information entered into business databases.
    • Developing software that can retrieve data from customer relational databases in a data warehouse.
    • Assessing the present performance level of a data warehouse and providing recommendations for enhancement.
  4. Proficiency in Data Analysis

    :

    Data analysis is a crucial aspect of any successful data warehouse. To ensure achievement, it is vital to recruit a data warehouse developer who possesses expertise in relevant areas such as data modelling, data mining, query optimization, and data transformation. Moreover, knowledge in business intelligence and analytics, as well as an awareness of data security and privacy, are critical qualities to consider when selecting the right developer.
    • Use the Eclipse IDE to tidy up your data.
    • Employ advanced analysis techniques to validate data.
    • Assist in managing and scrutinizing metadata.
    • Utilize Python and its corresponding libraries to maintain large datasets.
    • Develop stored procedures to utilize batch processing.
    • Develop tools for generating data visualizations.
    • Calculating simple statistical measures such as mean, median, mode, distribution, standard deviation, etc. are all instances of basic data analysis.

Data warehouse developers are highly sought after across multiple industries.

The global data warehousing industry was valued at more than $13 billion in 2018 and is predicted to grow at a rate of approximately 12% between 2019 and 2025, according to recent estimates. This substantial growth has resulted in a surge in demand for experienced data warehousing developers, with major multinational corporations such as Unifrax, Amazon, Accenture, Netflix, JP Morgan Chase Bank, and Flipkart all seeking highly skilled professionals to add to their teams.

Requirements That Must Be Met Without Exception

Skills that Require Physical Effort

We are seeking candidates who hold a Bachelor’s degree in Computer Science, Information Technology, Data Science, Statistics, Mathematics or a similar field. Alongside the mandatory degree, we also search for candidates with the following qualifications:

  • I have in-depth expertise in data warehousing, enterprise data management, and application development, especially in the arenas of extract-transform-load (ETL) and business intelligence (BI) employing Microsoft products.
  • Proficient in designing MS SQL queries and SQL Server applications using C#.NET, VB.Net, and ASP.NET frameworks.
  • Developing and administering the Unifrax data warehouse utilizing Microsoft SQL Server and Data Vault.
  • Improve the efficiency of the data warehousing environment.
  • Expertise in business intelligence (BI) tools such as Qlik, Power BI, Tableau, Microsoft Excel, etc.
  • Proficiency in designing relational and multidimensional data models.
  • Contributing to the developers Quality Assurance (QA) team by creating and administering test cases.
  • Production environment monitoring can ensure the accuracy and performance of the data warehouse.
  • Please provide separate evaluations of complexity.
  • Familiarity with the Snowflake data-sharing platform is advantageous in certain industries.
  • Experience with ETL tools (such as Stream sets and Informatica) is an added advantage.
  • Ability to make informed decisions based on evidence.
  • Understanding of agile and Scrum methodologies and expertise in technologies such as Apache Kafka, R-Hadoop, and Apache Spark are advantageous.

Interpersonal Skills

  • The ideal candidate should be capable of collaborating effectively within a team.
  • The ideal candidate should possess excellent communication skills.
  • Having a positive attitude and strong work ethic when addressing challenges is essential.
  • Exceptional skills in communication and leadership
  • Being skilled in time management and adaptable to changing circumstances are advantageous qualities for a candidate.
  • Proficiency in collaborating with cross-functional teams, representing diverse cultures and professions.
  • Receiving constructive feedback positively and possessing sociable nature can lead to increased productivity at work.
  • Ability to stay focused and determined to accomplish tasks

Conclusion

In today’s digital business landscape, it is crucial for companies to have a robust system in place that can effectively manage and process business intelligence data. The primary objective of developing a data warehouse is to help organisations gain better insights into their customers, anticipate business requirements, and enhance decision-making through the creation of logical and physical data models.

With the ever-increasing need for businesses to stay competitive, the demand for skilled data warehouse developers is on the rise. Therefore, it is vital for companies to ensure they are hiring the most qualified personnel available. The Works platform is an all-in-one human resources solution that streamlines the process of hiring, recruiting, and onboarding new employees, simplifying legal and tax obligations and compliance with local regulations.

Specialist Knowledge

At Works, we specialise in tech recruitment and have successfully placed remote engineers from various industries. Our comprehensive Human Resources services include assistance with hiring, invoicing, compliance, and taxes for remote and international workers, aiming to help you onboard the best remote developers to drive your most critical technological projects and initiatives.

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What makes Works Data Warehousing Developers different?
At Works, we maintain a high success rate of more than 98% by thoroughly vetting through the applicants who apply to be our Data Warehousing Developer. To ensure that we connect you with professional Data Warehousing Developers of the highest expertise, we only pick the top 1% of applicants to apply to be part of our talent pool. You'll get to work with top Data Warehousing Developers to understand your business goals, technical requirements and team dynamics.