Data Engineer - Client & Investor Lifecycle Management

Join Alter Domus, a global leader in integrated solutions for the alternative investment industry, as a Data Engineer within our Client & Investor Lifecycle Management team. In this pivotal role, you will directly impact client and investor relationships by transforming complex data into actionable insights, crucial for our KYC (Know Your Customer) and AML (Anti-Money Laundering) operations.

You will leverage cutting-edge technologies, including Fenergo API integration, data processing with Databricks and Apache Spark, and building insightful Power BI dashboards. Your responsibilities will include designing and maintaining scalable data pipelines and ETL processes, implementing data processing with Databricks, Apache Spark, and DataFrames following Medallion Architecture. You will also be responsible for ensuring data integrity through quality assessments and audits, creating executive-level Power BI reports and dashboards for key metrics, and maintaining comprehensive documentation for data processes and governance.

As we advance our cloud transformation, you will work with diverse technologies in a fast-paced environment, contributing to compliance, leadership strategy, and the integrity of client onboarding and due diligence.

**Key Responsibilities:**

• Lead Fenergo API integration for KYC/AML data extraction.
• Design, develop, and maintain scalable data pipelines and ETL processes.
• Implement data processing using Databricks, Apache Spark, and DataFrames.
• Conduct data quality assessments and root cause analysis.
• Architect and develop interactive Power BI dashboards and reports.
• Create visual representations of KPIs for KYC/AML processes.
• Maintain comprehensive documentation of data processes and solutions.
• Proactively resolve data-related issues.
• Implement data validation, quality control, and monitoring processes.

**Required Skills & Experience:**

• Bachelor's degree in a related field (Data Science, Computer Science, etc.).
• 5+ years of experience in Data Engineering, Data Analysis, or Reporting.
• Strong Python skills for data analysis and automation.
• Proficiency in Databricks and Apache Spark.
• Strong Power BI skills for executive-level dashboards.
• Expert-level SQL for querying and analysis.
• Solid understanding of data warehousing, ETL, data modeling, and Medallion Architecture.
• Experience with API integration.
• Experience with cloud platforms (Azure or AWS).
• Knowledge of Git for version control.
• Understanding of data governance and quality best practices.
• Strong problem-solving skills and adaptability.

**Nice to Have:**

• Databricks administration experience.
• Experience in Financial Services, KYC/AML processes, or regulatory compliance.
• Familiarity with machine learning concepts.
• Experience with graph data models.