Sutherland—Manager - Research

Job description

Description: Company Description: Sutherland’s Research—covering Equity Research, Credit Research, Investment Banking, and Business Research—Markets Insights, and Innovation division drives high-impact programs that address clients’ complex business and technology challenges. Sutherland Research and MII have made significant investments in building technology-led solutions that transform how data, research, and actionable insights are delivered for strategic and investment decision-making. Job Description: As part of the Sutherland Research and MII technology team, the Senior Data Engineer will design, develop, and maintain scalable data platforms that support financial research, analytics, automation and artificial intelligence solutions. The individual will work closely with domain specialists and client stakeholders to convert data from structured and semi-structured sources into reliable, governed, and analytically usable datasets. The role provides an opportunity to work on modern cloud data platforms (Azure/AWS/GCP), large-scale data transformation programs, financial datasets, AI-enabled applications and enterprise-grade data products. The Senior Data Engineer will be expected to provide technical leadership, independently manage data-engineering workstreams, mentor team members and ensure that solutions meet enterprise requirements for scalability, security, performance, governance and operational resilience. Job responsibilities - Lead enterprise data platforms across 3–5 large-scale programs end-to-end. - Architect data lakes, warehouses, lakehouses, and analytics products at scale. - Define reusable frameworks for ingestion, transformation, governance, and observability. - Mentor 5-10 member engineering teams across delivery, reviews, and issue resolution. Qualifications: To succeed in this position, the candidate must have: - 10+ years in data engineering, architecture, migrations, or integration. - Delivered 5+ enterprise data projects across cloud, lakehouse, or analytics platforms. - Strong expertise in Python, SQL, Spark, cloud, orchestration, and modelling. - Proven leadership in governance, security, CI/CD, monitoring, and stakeholder management. - Knowledge of finance, valuation, and investment research will be a plus.