Data Integration Consultant

Glint Tech Solutions • Philadelphia, PA

3d • Hybrid

About The Position

Our client is placing a Senior Data Integration Consultant embedded at a leading financial services organization in Philadelphia, PA. The consultant will work onsite as part of the client's data engineering effort, integrating client systems and data sources with an AI-powered Declarative Agentic Framework (DAF) and connected products. This is delivery work, not advisory — the consultant owns the data pipelines, warehouse structures, and integration points that the deployment depends on, and is fully accountable for data quality and reliability in production. Wall Street and financial industry background is a hard requirement. Candidates must reside in PA, NY, or NJ.

Requirements

• 10+ years in enterprise data architecture, data engineering, or solution architecture roles
• Direct financial services experience — ideally capital markets, asset management, or securities operations
• Must recognize and work fluently with financial terms such as reference data, corporate actions, and reconciliation without explanation
• Hands-on ETL and data warehousing expertise — Informatica, Snowflake, or comparable enterprise-grade tooling
• Production Python for data pipelines and integration work
• Experience with REST APIs, message queues (Kafka or similar), and containerized deployments (Docker)
• Proven track record owning end-to-end delivery from data analysis and architecture through production support
• Comfortable as the senior technical presence with client stakeholders from day one — no ramp-up period
• Excellent communication skills for coordinating with distributed and offshore teams

Nice To Haves

• Experience with AI platform integrations or agentic frameworks
• Familiarity with distributed or offshore team coordination
• Background in compliance-driven data environments within financial services

Responsibilities

• Design and build data integration pipelines connecting client source systems — reference data, pricing, transaction, custody, and similar — to the client's AI platform
• Own data warehouse and data lake architecture for the engagement including ingestion, transformation, and data quality rules
• Work hands-on with ETL tooling such as Informatica, Snowflake, or equivalent enterprise-grade platforms and cloud data platforms (AWS or Azure)
• Write production-grade Python for data processing and integration between on-prem and cloud systems
• Define data reconciliation and data lineage processes to ensure pipeline reliability and auditability
• Coordinate with the client's data engineering, ops, and compliance stakeholders as well as the AI deployment team
• Document architecture decisions and integration patterns to ensure work is defensible and repeatable across future deployments

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed