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About the Role

Build and maintain data pipelines for new private credit analytics products, covering data extraction, transformation, incremental refresh, and entity resolution from source to clean, validated data for consumption.

Responsibilities

• Design, build, and maintain production-grade ETL/ELT pipelines for data extraction, transformation, and loading from administration platforms into the analytics data model, handling high volumes and daily/intraday refreshes.
• Implement extraction logic for complex financial data, including loan balances, rate structures, pro-rata allocations, utilization calculations, and maturity dates.
• Implement change-data-capture (CDC) and incremental refresh patterns for near-real-time data delivery in client-facing products.
• Build pipelines to ingest, validate, de-duplicate, and integrate structured data from regulatory filings and third-party sources into the master data layer.
• Implement automated data quality checks (completeness, freshness, validation, integrity, duplicate detection) and build alerting for pipeline failures and anomalies.
• Collaborate with Data Architects and Platform Engineers to align logical design, physical implementation, and delivery 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 (Snowflake, Databricks, BigQuery, Redshift) and transformation frameworks (dbt).
• Experience with orchestration tools (Airflow, Dagster, Prefect) and CI/CD for data pipelines.
• Strong experience with CDC, streaming, or event-driven architectures.
• Solid understanding of data modelling (star schema, slowly changing dimensions, master data management).
• Experience in financial services data environments preferred.
• Experience with regulatory filing ingestion and parsing (e.g., XBRL, HTML extraction from public filings).
• Familiarity with loan-level data structures (credit agreements, facilities, tranches, pro-rata allocations).
• Experience building pipelines that serve external commercial clients.
• Cloud platform certifications (AWS, Azure, or GCP).

Skills

• Python
• SQL
• Snowflake
• Databricks
• BigQuery
• Redshift
• dbt
• Airflow
• Dagster
• Prefect
• CI/CD
• CDC
• Streaming
• Event-driven architectures
• Data modelling
• Star schema
• Slowly changing dimensions
• Master data management
• XBRL
• HTML extraction
• Loan-level data structures
• AWS
• Azure
• GCP

Location

• Hybrid

Work Type

• Hybrid
• Full-time

Experience Level

• 5+ years of professional data engineering experience

Salary/Compensations

• $87,500 to $145,000+

Benefits

• Industry-leading Alter Domus Academy offers six learning zones for every stage of your career, with resources tailored to your ambitions and resources from LinkedIn Learning.
• Support for professional accreditations.
• Flexible arrangements.
• Generous holidays.
• Additional day off for your birthday.
• Continuous mentoring along your career progression.
• Active sports, events and social committees across our offices.
• 24/7 support available from our Employee Assistance Program.
• The opportunity to invest in our growth and success through our Employee Share Plan.
• Additional local benefits depending on your location.

About the Company

• Alter Domus is a world-leading provider of integrated solutions for the alternative investment industry, serving 90% of the top 30 private market asset managers with over 6,000 professionals across 24 jurisdictions.
• The company focuses on innovation, unique work methods, and employee development, offering merit-based progression, open communication, and career support.

Equal Opportunity

• Alter Domus is an Equal Opportunity Employer. All qualified applicants receive consideration for employment without regard to race, color, religion, sex, national origin, disability, or protected veteran status.