Data Engineer

Role & responsibilities

Job Summary:

We are seeking a skilled Data Engineer to join our team. The ideal candidate will be responsible for developing and maintaining data products, ensuring their operational stability, and providing ongoing support. This role requires strong problem-solving skills, proficiency in data engineering tools, and the ability to work collaboratively within Agile delivery teams.

Key Responsibilities:

• Shape solutions in a fit-for-purpose way, following agreed principles and contributing to the Data Engineer development lifecycle.
• Support day-to-day testing and produce robust test plans to ensure the quality of data products and services.
• Perform data profiling and quality measurements, ensuring data quality and accuracy.
• Develop automated data ingestion routines, workflows/mappings, and data exploitation patterns.
• Own the stability of designed products, ensuring ongoing robustness, resilience, and stability.
• Identify, manage, and resolve issues preventing the delivery or continuous development of products.
• Support team growth by keeping abreast of market and industry trends, sharing knowledge, and taking responsibility for personal learning and development.

Requirements:

• Education: Bachelors or Master’s degree in a relevant field. Relevant certifications are preferred.
• Skills:
  
• Knowledge and experience with Azure/AWS Cloud data solutions.
• Proficient in SQL.
• Ability to develop and deliver complex visualisation, reporting, and dashboard solutions using tools like Power BI.
• Experience with ETL tools (e.g., Informatica).
• Experience in data modelling and transforming raw data into datasets and extracts.
• Knowledge of structured and unstructured data concepts.
• Experience in Agile methodologies.
• Experience: 5+ years as a Data Engineer or in a related role.

Competencies:

• Solution Shaping: Develop fit-for-purpose solutions and contribute to the data engineering lifecycle.
• Testing & Quality Assurance: Produce robust test plans and ensure the quality and live running of data products.
• Data Profiling & Quality: Perform data profiling and quality measurements, ensuring data accuracy.
• Automation & Workflows: Develop automated data ingestion routines and workflows.
• Stability & Resilience: Ensure the ongoing robustness and stability of data products.
• Issue Resolution: Identify, manage, and resolve issues preventing product delivery or development.
• Industry Awareness: Keep abreast of market and industry trends, sharing knowledge with the team.
• Collaboration: Work collaboratively with non-technical colleagues in an inclusive manner.