Senior Engineer, Data Engineering

Ares Management LLC; Mumbai; On-site; INR 3,500,000 - 6,500,000; Full time

Job summary

Ares Management Corporation is seeking an experienced Data Engineer to develop and maintain scalable data pipelines and cloud-based data platforms in our enterprise environment.

You will collaborate with global teams to design, implement, and optimize data solutions, ensuring quality, governance, and reliable analytics for reporting and decision-making.

Qualifications

• Bachelor's degree or equivalent in CS/Engineering/IS/Data Science or related.
• 6–10 years hands-on data engineering in financial services or equivalent.
• Designing and deploying enterprise-scale data pipelines (batch and streaming).
• Experience with Azure Databricks, PySpark, Delta Lake, Python and SQL.
• Proven ability to own technical delivery within an enterprise data model.
• Familiarity with CI/CD, IaC (Terraform), GitHub Actions, Azure DevOps, and testing practices.

Responsibilities

• 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.

Skills

Data engineering

ETL/ELT design

Python programming

SQL proficiency

Cloud data platforms

Stakeholder collaboration

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or related discipline

Tools

Azure Databricks

PySpark

Delta Lake

Python

SQL

Azure Data Factory

Job description

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

Primary functions & responsibilities

• 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.

Qualifications

• 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

Partner, Chief Information Officer