S&P Global | Hiring | Data Engineer | BigDataKB.com | 07-04-2022

Position summary

The BizOps Data Engineer is responsible for laying down the foundation of a database and its architecture. They will be expected to partner with the Data Architect in a wide range of requirements and apply relevant database techniques to create a robust architecture. Afterward, the data engineer begins the implementation process and develops the database from scratch. After periodic intervals, they also carry out testing to identify any bugs or performance issues.

The data engineer will be tasked with maintaining the database and ensuring that it works smoothly without causing any disruption. Data engineers will also support the data science team by constructing dataset procedures that can help with data mining, modelling, and production. A key role for this position is to focus on continuing to enhance the quality of data.

Duties & accountabilities

• Data Architecture – Use a systematic approach to plan, create, and maintain data architectures while also keeping it aligned with business requirements.
• Collect Data – Before initiating any work on the database, must obtain data from the Data Architect. After formulating a set of dataset processes, store optimized data.
• Conduct Research – Conduct research in the industry to address any issues that can arise while tackling a business problem.
• Improve Skills – Continue to have the knowledge and prowess to work in any development environment regardless of programming language. Similarly, keep up to date with machine learning and algorithms.
• BI Visualizations – Proficient in Tableau (preferred) to assist BI team with meaningful tables that generate valuable business insights.
• Create Models and Identify Patterns – Use descriptive data model for data aggregation to extract historical insights and create predictive models where applicable. Additionally, identifying hidden patterns from stored data.
• Automate Tasks – Dive into data and pinpoint tasks where manual participation can be eliminated with automation.

Experience/Minimum Requirements:

• BS/BA in Computer Science, Statistics, Data Management, or a related field
• 5-7 years of proven experience in:
  • Data warehouse, modelling and design, including SQL development and database administration
  • Programming & ETL tools – Alteryx (required) and/or Python, or R
  • Hands-on experience with SQL database design, schema design and dimensional data modelling

• Knowledge of systems development, including system development life cycle, project management approaches and requirements, design and testing techniques
• Ability to implement common data management and reporting technologies
• Data mining and BI visualization tools (Tableau)

Not required, but other skills/abilities:

• Experience with ontology or semantic systems (e.g. RDF, RDFS, OWL, SPARQL, SHACL)
• Extensive knowledge of modern database technologies (e.g. Triple Stores, Labeled Property Graphs, Hypergraphs)
• In-depth experience with API technologies (e.g. GraphQL, gRPC)
• Understanding of predictive modelling, NLP/text analysis, Machine Learning

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Equal Opportunity Employer:

S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to: [email protected] and your request will be forwarded to the appropriate person.

US Candidates Only:

The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law.