Required Skills & Experience
- 14+ years of experience in data engineering, architecture, and analytics, including substantial experience owning delivery and/or account leadership.
- Proven hands-on expertise across the full data stack: SQL, Python, ETL/ELT (Alteryx, Informatica, Azure Data Factory, dbt), and cloud data platforms (Azure, AWS, or GCP — Snowflake, Databricks, Synapse, Redshift, BigQuery).
- Deep architectural experience — data lake/warehouse/lakehouse design, enterprise/common data models (CDM), and data governance & catalog tooling (Collibra, Purview, Alation).
- Strong analytics/BI background — Power BI, Tableau, Qlik — and experience enabling self-service and advanced analytics/AI-ML use cases.
- Demonstrated experience managing multiple client accounts or a portfolio of engagements simultaneously, including account growth, delivery governance, and executive relationship management.
- Track record leading large data transformation programs end-to-end — from strategy and roadmap through architecture, build, and adoption.
- Strong pre-sales/solutioning capability — proposals, RFP responses, staffing plans, and commercial/delivery models.
- Excellent stakeholder management and communication skills — equally credible with C-level executives and hands-on technical teams.
- Demonstrated people leadership — building, mentoring, and scaling multi-disciplinary data teams across engagements.
- BFSI domain knowledge preferred — regulatory/risk reporting, core banking data, and compliance frameworks (BCBS 239, Basel, CCAR).
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Data/Information Systems, Engineering, or a related field; MBA a plus.
- Cloud or architecture certifications (Azure/AWS/GCP, TOGAF) and/or data management certification (DAMA/CDMP).
- Prior experience in a consulting, systems-integrator, or professional-services environment managing a multi-client portfolio.
- Exposure to GenAI/LLM-driven analytics strategy and its application within regulated industries.
