Data Engineer

Responsibilities

• Data Extraction and Data Processing
  
  • Experience with Elastic Stack (ELK), data modelling, data warehousing, and ETL processes is a must.
  • Proficiency in programming languages such as Python and SQL.
  • Experience with cloud-based data solutions such as AWS or Azure.
  • Basic understanding of Machine Learning methodologies and pipelines.
• Data Quality Assurance
  
  • Maintain and monitor data pipelines, addressing recurring issues and deeper data problems.
  • Address and fix vulnerability issues in data pipelines to ensure data security.
  • Proactively create alerts and notifications to identify potential issues in data pipelines.
• Data Communication
  
  • Communicating analytical insights through sophisticated synthesis and packaging of results (including PPT slides and charts) with consultants, collecting, synthesising, and analysing case team learning & inputs into new best practices and methodologies.
  • Collaboration with Cross-Functional teams to include analysts and business stakeholders to create actiona
  ...

Responsibilities

• Data Extraction and Data Processing
  
  • Experience with Elastic Stack (ELK), data modelling, data warehousing, and ETL processes is a must.
  • Proficiency in programming languages such as Python and SQL.
  • Experience with cloud-based data solutions such as AWS or Azure.
  • Basic understanding of Machine Learning methodologies and pipelines.
• Data Quality Assurance
  
  • Maintain and monitor data pipelines, addressing recurring issues and deeper data problems.
  • Address and fix vulnerability issues in data pipelines to ensure data security.
  • Proactively create alerts and notifications to identify potential issues in data pipelines.
• Data Communication
  
  • Communicating analytical insights through sophisticated synthesis and packaging of results (including PPT slides and charts) with consultants, collecting, synthesising, and analysing case team learning & inputs into new best practices and methodologies.
  • Collaboration with Cross-Functional teams to include analysts and business stakeholders to create actionable insights.

Personality Profile

• Conscientiousness: Process-Oriented
  
  • Demonstrates thoughtfulness, meticulousness, and a strong sense of responsibility.
  • Highly organised, detail-oriented, and adept at managing multiple tasks and deadlines.
  • Proactive in approach with reasonable impulse control.
  • Consistently delivers high-quality results with a strong work ethic.
  • Committed to continuous self-improvement through formal and informal learning opportunities.
• Sturdiness: Consistently Producing Quality Work
  
  • Demonstrates resilience and perseverance in completing tasks effectively.
  • Consistently produces high-quality work, even under pressure or challenging circumstances.
  • Maintains focus and determination to achieve goals and meet deadlines consistently.
• Quantitative: Analytical and Data-Driven
  
  • Possesses strong quantitative skills and analytical mindset.
  • Comfortable working with numerical data and conducting statistical analysis.
  • Applies quantitative methods to solve complex problems and derive actionable insights from data.
  • Utilises mathematical models and tools to optimise processes and improve efficiency.

Experience and Qualifications

Minimum Qualifications

• 2+ years of data pipeline management experience.
• Proficiency in Python development (2+ years).
• Exposure to Google Cloud Platform (GCP).
• Ability to write complex SQL queries.
• Understanding of data management standards.

Preferred Qualifications:

• 2-4 years of Data Engineering experience.
• Consulting experience is a plus.
• Knowledge of Spark cluster management.
• Hands-on experience with tools like Airflow.
• Proficiency in Elastic Stack (ELK).

Categorisation Details

○ Industry Type: Health and Wellness Technology
○ Department: Operations
○ Employment Type: Full Time, Permanent
○ Education: Relevant Degree in Business, Data Science, Data Engineering or Computer Science