Senior Data Engineer

Join a team that values your ambition and empowers your growth!

At Corient, we help high- and ultra-high-net-worth individuals and families to enjoy a full life, while enabling them to preserve their wealth for future generations, and provide for the people, causes and communities they care about. We focus on exceeding expectations, simplifying lives, and establishing legacies that last for generations. We are always looking for talented and motivated individuals to join our team.

If you want to work for a company that values your contributions and supports your growth, we would like to meet you.

The Senior Data Engineer designs and builds scalable, reliable data pipelines and models enabling enterprise analytics, reporting, and data quality initiatives.

• Technical data operations and execution. Implement engineering best practices across data pipelines, modeling, data quality, lineage, metadata management, documentation and operational monitoring. Oversee sprint planning, backlog prioritization, and execution across multiple data initiatives.
• Enterprise Data Layer operation. Design, architect, develop, and maintain robust and scalable data pipelines, transformations, models, and workflows. Develop and operate automated data jobs for data science, analytics, and reporting purposes.
• Data QA operations. Implement automated QA analytics, reconciliations, and monitoring to ensure data integrity across enterprise platforms and enterprise data layer. Establish data quality frameworks including validation, monitoring, reconciliation, and alerting, ensuring strong governance around data accuracy, completeness, and timeliness across critical datasets.
• Cross-functional data engineering support. Support Analytics, Operations, and Business teams in data initiatives, deeply understanding functional requirements and delivering data solutions that meet these needs in a timely and reliable fashion.

• 6+ years of experience in data engineering, data platform development, or analytics engineering.
• Background in Financial Services, consulting, or high‑growth technology environments preferred.
• Distinguished academic track record in data, computer science, or related discipline.
• Proven experience building enterprise data platforms supporting reporting and analytics.
• Hands‑on experience with data modeling, ETL/ELT pipelines, analytics engineering, and data operations.

• Proficiency in data engineering languages, frameworks, and tooling, including SQL, Python, and DBT.
• Strong command of best practices for data modeling, data pipelines, data transformations, and data quality frameworks to support scalable, enterprise grade data products.
• Strong analytical, problem-solving, and critical thinking skills.
• Effective communication, both orally and in writing.
• Strong documentation and attention to detail.
• Ability to work independently and collaboratively in a fast-paced, dynamic environment.