Senior Engineer, Data Engineering

Over the last 20 years, Ares’ success has been driven by our people and our culture. Today, our team is guided by our core values – Collaborative, Responsible, Entrepreneurial, Self-Aware, Trustworthy – and our purpose to be a catalyst for shared prosperity and a better future. Through our recruitment, career development and employee-focused programming, we are committed to fostering a welcoming and inclusive work environment where high-performance talent of diverse backgrounds, experiences, and perspectives can build careers within this exciting and growing industry.

Job Description

• 
  Develop and maintain scalable data pipelines, ETL/ELT processes, and data integrations.
• Support ingestion of structured and unstructured data from internal and external sources.
• Assist with building and optimizing cloud-based data solutions and enterprise data platforms.
• Work closely with global teams on design, architecture and build out of data platform.
• Partner with business teams to understand reporting and analytics requirements.
• Monitor data quality, performance, and reliability across data environments.
• Contribute to data governance, lineage, and documentation initiatives.
• Participate in code reviews and engineering best practices.

Education: Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related discipline. Equivalent relevant experience will be considered.

Experience Required: 6 to 10 years of hands-on data engineering, data solutions, or financial technology experience, ideally within financial services, asset management, accounting, investment operations, or another controlled enterprise data environment.

Hands-on experience designing, developing, deploying, and supporting enterprise-scale data pipelines using Azure Databricks, PySpark, Delta Lake, Python, SQL, and Azure Data Factory, including both batch and streaming workloads.

• Hands-on Databricks experience, including notebooks, workflows/jobs, Spark concepts, Delta Lake patterns, and production support.
• Python and/or PySpark for transformation, validation, automation, and testing.
• Strong ETL/ELT, data modeling, integration, and curated-data-layer experience.
• Experience building domain-specific transformations, integrations, data products, validation, reconciliation, monitoring, and controls.
• Ability to own technical delivery while working effectively within a broader enterprise data and reporting operating model.
• Working knowledge of Unity Catalog, metadata, lineage, master/reference data, governance, controls, and auditability concepts.
• Experience structuring governed data for dashboards, reports, extracts, downstream applications, operational workflows, and analytics
• Strong understanding of CI/CD, Infrastructure-as-Code (Terraform), GitHub Actions, Azure DevOps, automated testing, release management, and environment promotion strategies supporting both platform and data engineering workloads.

Reporting Relationships

There is no set deadline to apply for this job opportunity. Applications will be accepted on an ongoing basis until the search is no longer active.