Data Engineer
Key Responsibilities
- Together with the Data Scientist, will partner with business leaders to ensure an in-depth understanding of requirements and the data required to create advanced analytics solutions.
- Enable automation of advanced analytics solutions using data science algorithms and data structures associated with advanced analytics.
- Creates and maintains data pipelines which will involve data sourcing, extraction, transformation, profiling, storage, updating, indexing and maintenance of the advanced analytics data platform.
- Develops and automates metrics, dashboards and reports that consistently monitor and show data governance initiative trends (e.g. data quality reports) through the implementation of guidelines, standards and best practices for data management.
- Process raw, structured and unstructured data at scale (including writing scripts, web scraping, calling APIs, writing SQL queries etc.) into a form suitable for analysis then consolidate into a data platform for consumption by advanced analytics initiatives.
- Drive innovation through continuous re-engineering of data and advanced analytics jobs, performance tuning and optimizing the application of data across all advanced analytics layers (acquisition, staging, profiling, cleansing, analysis, modelling, output).
- Works with Business customers to understand business requirements and implement data solutions with business owners through the development of key business questions and datasets that will be used to answer those questions.
- Helps implement data management projects by working with key stakeholders (Technology and Business) and provides expert input, guidance and feedback in such projects.
- Work closely with product owners and business analysts to develop insights and data solutions
- Develop and maintain technical documentation/manuals on configurations, setups and deployment of various advanced analytics solutions
Read More>>>Top 4 Reasons Why PMP Certification Will Boost Your Career In 2025
Academic & Professional
Education
- Bachelor’s Degree in Computer Science, Data Science, Information Technology, Engineering, Mathematics or equivalent combination of education and experience. RQ
- Master’s degree Data Science, Advanced Analytics Related Fields or Related.AA
- Professional Certifications Any Data Engineering related certifications. AA
Experience
- Total Minimum No of Years’ Experience Required: 3 years
- Detail Minimum[1] No of Years Type
- Data Warehousing 2 ES
- Data Analytics and Modelling 2 ES
- Experience in use of any ETL tool e.g., Oracle ODI/Microsoft SSIS/SAP Data services/Alteryx or any other tool. 2 ES
- Programming (Python and(or) R) 2 ES
- Data Visualization e.g. OBIEE/Power BI/Tableau/SAP BI tools 2 ES
- SQL (Oracle PL/SQL) 2 ES
- Data Governance/Data Quality 2 DE
Read More>>>The Power Of Digital Marketing: Millicent’s Success Story
How to Apply
Click Here to Apply