An international utilities company is looking for a Data Engineer who has at least 3 years of relevant experience. This is an excellent opportunity to join a global concern and form part of their Business Systems team. This is predominately a work from home role with occasional meetings in the office.
You will play a pivotal role in building and operationalizing the minimally inclusive data necessary for enterprise data and analytics initiatives. A key focus will be on building, managing, and optimizing data pipelines and subsequently moving the pipelines into production for use across the business.
Reporting to the Data and Information Manager you will collaborate with Group IT, key business stakeholders, and subject matter experts to creatively plan and deliver optimal analytics and data solutions. Adopting a selling approach, you will have the responsibility for ensuring a better understanding of data and analytics across the Group and the benefits of effective management practices.
What else will you do?
Build data pipelines – architecting, creating, and maintaining managed data pipelines
Drive automation through effective metadata management, using innovative and modern tools, techniques, and architectures to automate the most-common, repeatable, and tedious data preparation and integration tasks partially or completely in order to minimize manual and error-prone processes and improve productivity.
Assist with renovating the data management infrastructure to drive automation in data integration and management.
Collaborate across departments, working with varied stakeholders, notably the Business Stakeholders teams and business (data) analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
Educate and train. Curious and knowledgeable about new data initiatives and how to address them, you will be responsible for proposing appropriate (and innovative) data ingestion, preparation, integration, and operationalization techniques. Training counterparts such as data analysts, LOB users, or any data consumers in data pipelining and preparation techniques, will also be required for easier integration.
Participate in ensuring compliance and governance during data use, ensuring that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives. Working with data governance teams (and data stewards within these teams) you will participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse.
Act as a data and analytics evangelist – with a blend of data and analytics “evangelist,” “data guru” and “fixer” to promote the available data and analytics capabilities and expertise to business unit leaders and to educate them in leveraging these capabilities in achieving their business goals.
The successful applicant will have a degree in Computer Science, IT, or a similar field (Statistics, Mathematics) and 3+ years of relevant working experience.
Strong experience is essential with various data management architectures (such as Data Warehouse, Master Data Management, Data Lake, Data Hub), working with large, heterogeneous datasets in building and optimizing data pipelines, data architecture, and integrated datasets using traditional data integration technologies and popular database programming languages including SQL/PL/SQL. Strong ability to design, build and manage data pipelines as well as the ability to build quick prototypes and automate pipeline development is important.
Demonstrated success in working with Spark Ecosysem (Databriks), large heterogeneous datasets, working with Dev Ops capabilities and collaborating across a business to integrate analytics and data science into business processes and workflows will be required.
Basic experience working with BI software tools, working with data governance/quality teams, and exposure to hybrid deployment – Cloud and On-Premise advantageous.
Success in this role will not only depend on your knowledge but how you go about your work.