Data Engineer
About The Position
The Data Engineer will build and maintain the data pipelines that power a suite of private credit analytics products. The role covers the data-in-motion layer, from extracting data from large-scale loan administration systems through transforming it and landing clean, validated, and reconciled data in the platform for downstream use. Responsibilities include preparing analytics-ready data, implementing incremental refresh logic for near-real-time delivery, and resolving entities across multiple sources. Pipelines must support tens of thousands of live records with daily or intraday refresh requirements.
Requirements
- 5+ years of professional data engineering experience building production pipelines at scale.
- Expert proficiency in Python and SQL.
- Hands-on experience with modern cloud data platforms such as Snowflake, Databricks, BigQuery, or Redshift and transformation frameworks such as dbt.
- Experience with orchestration tools such as Airflow, Dagster, or Prefect, and CI/CD for data pipelines.
- Strong experience with CDC, streaming, or event-driven architectures.
- Solid understanding of data modelling, including star schema, slowly changing dimensions, and master data management.
- Experience in financial services data environments is preferred.
Nice To Haves
- Experience with regulatory filing ingestion and parsing, such as XBRL or HTML extraction from public filings.
- Familiarity with loan-level data structures, including credit agreements, facilities, tranches, and pro-rata allocations.
- Experience building pipelines that serve external commercial clients, not only internal BI.
- Cloud platform certification in AWS, Azure, or GCP.
Responsibilities
- Design, build, and maintain production-grade ETL/ELT pipelines that extract, transform, and load data from core administration platforms into the analytics data model.
- Implement extraction and transformation logic for complex financial data, including loan balances, rate structures, pro-rata allocations, utilisation calculations, and maturity dates.
- Implement change-data-capture (CDC) and incremental refresh patterns to deliver near-real-time data without full reloads.
- Build pipelines to ingest and validate structured data from regulatory filings and third-party sources, de-duplicate it against the primary dataset, and integrate it into the master data layer.
- Implement automated data quality checks for completeness, freshness, range validation, referential integrity, and duplicate detection.
- Build alerting for pipeline failures and anomalies.
- Collaborate with the Data Architect and Platform Engineer to align logical design, physical implementation, and delivery requirements.
Benefits
- Support for professional accreditations.
- Flexible arrangements and generous holidays, plus an additional day off for your birthday.
- Continuous mentoring along your career progression.
- Active sports, events, and social committees across offices.
- 24/7 support through the Employee Assistance Program.
- Opportunity to invest in the company's growth and success through the Employee Share Plan.
- Additional local benefits depending on location.
- Access to the Alter Domus Academy, with six learning zones and resources including LinkedIn Learning.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
