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We are seeking highly skilled and experienced Azure Data Engineers to join a newly formed group concentrating on Data. Within this role you will be a key member of the team, working on a complex and challenging project within the Financial Services/Capital Markets industry. The primary focus of the role would be on building resilient, reusable Data Pipelines to extract, load, and transform raw data into a relational data model. The successful candidate will work across complex, multi-source datasets including loan servicing systems, property and valuation platforms, collections systems, and third-party data providers, delivering reliable and auditable data at scale.
Job Responsibility:
Serve as the team’s ADF, Databricks, Python, PySpark & Spark SQL technical expert
Responsible for day-to-day collection & ingestion of raw data into corporate data assets
Work with the team to formalize data flows and data standards
Enable trusted datasets for portfolio analytics, asset strategy, finance, and risk
Supervise all data ingestion & integration processes from source to target including the data warehouse, data lake, etc
Performance tune and optimize all data ingestion and data integration processes
Partner with Data Stewards and Business Analysts to understand the nature of the data being handled and what an optimal Data Pipeline for it should look like
Design solutions that are aligned to the target state Data Architecture
Requirements:
Degree in Computer Science, Information Systems, Data Science, or a related field is preferable
Proven experience building resilient, reusable Data Pipelines as a Data Engineer or equivalent
Resourceful, motivated self-starter with the ability to collaborate across business and technology
Strong analytical, verbal, and written communication skills
A background in financial data domains (IBOR/ABOR, transactions, market data, reference data)
Strong experience as a Data Engineer within Real Estate, Credit, Banking, or NPL Asset Management