Data Engineer

Required Skills & Responsibilities:

As a Data Engineer, your primary responsibilities include implementing data systems that support business intelligence and analytics. This role involves:

Specific Responsibilities:

• The ability to construct queries/conduct in-depth data analysis to assist in validating technical specifications and investigate data issues identified by end users and / or the Business Intelligence team.
• Strong understanding of DWH concepts and implementation methodology using, Data vault, Snowflake Schema and Star Schema design pattern.
• Develop Data complex transformation, analytical and reporting solutions.
• Data and model analysis of Ncino and ThM to develop the medallion architecture set out by the MI/BI workstream.
• Daily monitoring and maintenance of the data ingestions across environments as the estate grows as a result of the capabilities built within Ncino and ThM.
• Reconcile, validate pipelines from source to reporting (Power BI models, Paginated Reporting, financial models).
• Document and execute data governance practices (lineage, code documentation, glossary of terms).
• Abiding by Coding & Process Standards and working with DevOps practices.
• Experience in implementation and the development of the complete Data Warehousing solutions using the MSBI stack (SSIS, SSAS, SSRS) and Power BI.
• Strong experience in ETL framework and development adhering to best practices and standards.
• Performance Optimization: Identifying and implementing optimizations to enhance the performance of BI/DW systems, ensuring timely and accurate data delivery.
• Experience with any cloud environments e.g. AWS/Azure/GCP

Skills and Experience:

• High energy levels, enthusiasm, a can-do attitude, and the ability to drive activity through to completion on time with a high level of customer satisfaction.
• Excellent interpersonal, communication and presentation skills – verbal and written.
• Good working knowledge of database design and data warehousing methodologies.
• Ability to demonstrate development practices and practical experience in a complex dataset environment in financial services.
• Following code standards, following up on code reviews.
• Experience of end to end BI and Data engineering development, support and maintenance.
• Data modelling analysis and relationship understanding to be able to construct complex data relationships.
• ETL and data pipeline development.
• Experience with ETL/ELT workflows and data pipeline automation.
• Financial services experience is desirable.

Language skills:

• Strong T-SQL (triggers, views, stored procedures, user defined functions, DDL, DML).
• Strong SQL Server troubleshooting skills/ Strong analytical skills.
• Strong programming skills in Python & SQL.
• Preferred Azure cloud experience within the Data Analytics space.
• Knowledge of SSAS, SSRS, SSIS, Power BI to support in transformation reverse engineering.
• Databricks hands on experience on data ingestion from API.