Data Integration Consultant

Location: Hybrid – Philadelphia, PA (1 day onsite/week) | Candidates from PA, NY, NJ only

Company Overview

Glint Tech Solutions is a women-owned global staffing and IT recruiting firm connecting top technical talent with leading enterprise clients across the United States and Canada.

Project Description

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.

Key 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

Mandatory Skills

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-Have Skills

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

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