Artificial Intelligence (AI), Bridge Building, Channel Strategies, Civil Engineering, Consulting, Data Management, Data Modeling, Data Quality, Data Science, Documentation, Enterprise Architecture, Interviewing Skills, Leadership, Machine Learning, Machine Tool, Market Research, Metrics, Onboarding, Performance Analysis, Performance Metrics, Program Control, Quality Management, Standards Development, Taxonomies, Team Lead/Manager, Variance Analysis
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
We are looking for a Senior Manager / Associate Director to lead delivery workstreams within a large-scale enterprise Data Governance, Architecture & Controls Program.
Responsibilities:
- Lead pods focused on data lineage documentation (consumption through ADS to system of origin), target-state ADS landscape and architecture design, and aggregation layer controls including DQ rules, variance analysis, and anomaly detection.
- Shape the data modeling and architecture decisions that underpin the target-state ADS landscape, working with enterprise architecture to evolve domain and subdomain taxonomy.
- Conduct SME interviews across engineering and business data offices, translate enterprise data management policy into actionable delivery and build plans, and manage a small team of analysts through design and implementation.
- Operate as the bridge between engineering, enterprise architecture, and data office stakeholders, and present findings and recommendations directly to senior client leadership.
- Define and standardize repeatable playbooks, templates, and execution frameworks for data lineage harvesting and Authoritative Data Source (ADS) onboarding to ensure consistency across multiple pods.
- Collaborate with Enterprise Architecture and Tooling teams to evaluate, select, and drive the adoption of data governance and lineage platforms.
- Establish, monitor, and report on key performance indicators (KPIs) and operational metrics reflecting the progress of lineage coverage, ADS compliance, and data quality improvement to senior stakeholders.