Data Governance Manager (a.i.)
Role details
Job location
Tech stack
Job description
The Digital & Change team is expanding in line with Triple Jump's growing focus on digitalization and data. As part of this, we are strengthening our data governance capabilities and further developing our Azure-based data platform (Lakehouse, Synapse, Databricks, Power BI) to support all operational, client, and corporate reporting needs.
As a Data Governance Manager (a.i.), you are responsible for establishing and embedding a strong data governance framework across the organization. You ensure data is accurate, consistent, secure, and effectively managed by defining standards, ownership models, and quality controls.
You will work closely with Digital & Change, operations, risk, and investment teams to align data practices with business and regulatory requirements, enabling a single source of truth. You contribute to company-wide initiatives with global impact and report to the Head of Digital & Change.
Key responsibilities
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Data Governance & Strategy: Develop and implement a firmwide data governance program, including data standards, ownership models, quality controls, and authoritative data sources ("book of record"). Define a data dictionary and establish governance processes to ensure consistency and accountability in how data is defined, collected, and used.
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Data Quality & Integrity: Define and enforce data quality rules, lineage documentation and standards for critical investment and business data. Maintain a single source of truth through validation rules, monitoring, and regular audits to ensure critical data is exact, consistent, and readily available across the organization.
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Data Infrastructure Oversight: Oversee internal data infrastructure - data warehouses, data lakes, ETL/ELT pipelines, and related platforms. Ensure systems are scalable, efficient, and aligned with the firm's analytics and reporting needs. Lead evaluation and ongoing management of data and analytics vendors, including quality, cost, and service standards.
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Compliance & Security: Ensure data management practices comply with all relevant financial regulations, data privacy laws, and internal policies. Implement robust data security and access controls to protect sensitive information and support audit readiness.
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Cross-Functional Collaboration: Partner with business teams to align data strategy with business needs. Integrate data solutions into operational workflows and agreed-upon processes., * A competitive daily fee, aligned with market standards in the Impact Investing sector, depending on experience and scope of the assignment;
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A clearly defined, short-term consultancy engagement with a high-impact mandate;
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Flexibility to organize your work independently within the agreed scope and deliverables;
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A dynamic, multi-cultural and diverse working environment with exposure to international teams and projects;
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Collaboration with experienced professionals in an impact-driven organization
Requirements
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Experience: 10+ years in data management, data governance, or data engineering - with at least 5 years in a leadership role - preferably within asset management or financial services. Experience in Fund accounting is a strong plus.
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Domain Knowledge: Strong understanding of investment data, portfolio analytics, and financial data concepts. Familiarity with regulatory requirements affecting data (e.g., data privacy, financial reporting standards).
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Technical Expertise: Hands-on experience with data architecture and management tools, specifically Microsoft Azure, Databicks, Git and Python. Ability in data governance practices - data cataloging, master data management, and metadata management - is essential.
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Leadership & Communication: Proven ability to lead cross-functional teams and influence senior stakeholders across functions. Excellent communication skills to translate complex data concepts into clear business terms, bridging technical teams and business stakeholders.
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Analytical & Strategic Skills: Exceptional problem-solving abilities with a strategic mindset. Track record of implementing data solutions that improve operational efficiency and drive innovation.