ENVIRONMENT:THE technical expertise of a proactive & solutions-driven Mid-Senior Data Engineer is sought by a dynamic FinTech company to primarily support its Client Engagement team. Your core role will be to provide insight and make recommendations around utilising Business Intelligence best practice and Data Modelling techniques. You will also be expected to drive a positive & supportive culture towards the Client Engagement team, ensuring customers are satisfied with their service delivery. The ideal candidate must have Matric/Grade 12 and any relevant Technical Degree/Diploma or Formal Business/Technical Analysis training, or relevant Data Certification will prove beneficial. You must have strong business acumen, digital literacy, Windows operation skills, Office 365 Team, Word, Excel, PowerPoint with solid SQL (ANSI preferably T-SQL), Dimensional Modelling (Kimble methodology), RDBMS Architecture, OLTP and OLAP concepts, Data integration concepts (ETL / ELT), knowledge of the Financial and Investment industries and experience with information classification and Taxonomy. Remote work on offer.DUTIES:Data Management & BI

  • Provide data management services to the Client Engagement team.
  • Provide input to data quality deliverables, conduct root cause analysis into anomalies & provide feedback to data governance facilitator.
  • Identify and recommend data cleansing opportunities.
  • Identify and recommend new metrics, attributes, datasets to support business intelligence requirements.
  • Drive a Data-Driven approach to decisions.
  • Drive on a Right-Data at the Right-Time principle to Intelligence.

Provide Business Insight to support the Client Engagement Team –

  • Use approved technology to build dashboards and data models.
  • Work with the Data Engineers to improve current products to increase usage.
  • Provide feedback to wider team to collaborate on digital strategy of Data Assets.
  • Gather business needs and clearly documenting expected outcomes.

REQUIREMENTS:Qualifications

  • Matric / Grade 12 essential.
  • Technical Degree or Diploma (in related industry) advantageous.
  • Formal Business/Technical Analysis training advantageous.
  • Relevant Data Certifications advantageous.

Experience/Skills

  • Excellent digital literacy.
  • General Windows operating skills.
  • Good knowledge of the Office 365 suite of tools (Teams, Word, Excel, PowerPoint).
  • Solid knowledge of:
  • SQL (ANSI preferably T-SQL)
  • Dimensional Modelling (Kimble methodology)
  • RDBMS Architecture
  • OLTP and OLAP concepts
  • Data integration concepts (ETL / ELT)
    • Knowledge of the Financial and Investment Industry.
    • Understanding of general business terminology.
    • Experience engaging with stakeholders at all levels of business.
    • Able to present and communicate concepts and ideas clearly to an audience.
    • Drive to gather accurate and comprehensive information.
    • Able to collate and organise information.
    • Experience in information classification and Taxonomy.
    • Able to interpret and simplify information.
    • Keen understanding of Data terminology and principles.

ATTRIBUTES:

  • Good communication skills (verbal and written).
  • Good interpersonal skills.
  • Analytical thinking.
  • Facilitation skills.
  • Creative thinking.
  • Strong problem-solving skills.
  • Negotiation skills.
  • Critical thinking.

While we would really like to respond to every application, should you not be contacted for this position within 10 working days please consider your application unsuccessful.COMMENTS:When applying for jobs, ensure that you have the minimum job requirements. OnlySA Citizens will be considered for this role. If you are not in the mentioned location of any of the jobs, please note your relocation plans in all applications for jobs and correspondence. Please e-mail a word copy of your CV to [Email Address Removed] and mention the reference numbers of the jobs. We have a list of jobs on [URL Removed] Datafin IT Recruitment – Cape Town Jobs.

Desired Skills:

  • Data
  • Engineer
  • SQL

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