Data Engineer

Job Summary

The Data Engineer is a core part of the Engineering team and is responsible for supporting the continued development and maintenance of our client's data models and pipelines. This role is a key part of building a world-class data platform that provides access to clean and efficient data across all teams.

Key Responsibilities

• Building data pipelines to move and transform data from various sources to storage systems as per ongoing business objectives and requirements.
• Developing and documenting solutions with clear, well-defined flowcharts, layouts, diagrams, and/or charts.
• Support and maintain any data platform failures or issues in the data systems by troubleshooting, proposing, and implementing solutions.
• Collaborate closely with other teams across the business, ensuring clear communication and understanding of business requirements.
• Continually staying up to date with the latest technologies and methodologies within data engineering to propose and implement innovative solutions.
• Identifying and implementing process improvements.
  
  

In addition to the above, a Senior Data Engineer also:

• Supporting the Lead Data Engineer with coaching and mentoring junior team members.
• Collaborating with analysts and stakeholders to understand data requirements
• Developing frameworks to support data systems and assist with extending functionality as our client continues to grow.
• Contributing to and supporting the strategic planning of data architecture as part of quarterly planning.
• Leading data projects end-to-end, ensuring ongoing collaboration with relevant stakeholders, and ensuring timelines are met.
• Promoting and presenting data engineering work both within the team and with external teams
• Implementing Data Quality and Validation checks to improve the reliability of the data platform, ensuring optimal performance of data systems
• Implementing and maintaining data security and compliance measures
  
  

Requirements:

• Knowledge and understanding of Data Warehousing concepts and methodologies
• Working knowledge of Python and SQL
• Experience and familiarity with data modelling techniques such as Star and Snowflake Schemas
• Experience with platforms such as Snowflake, dbt, and Airflow
• Familiarity with cloud platforms - Azure, AWS, GCP
• Experience with code version control tools like GitHub, GitLab
• Strong verbal and written communication skills to work effectively within cross-functional teams.
• Ideally, experience working within the financial services domain or similar.
• Experience working in an agile environment.