Data Architect Data Modeler

Argyllinfotech

NULL, NJ

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JOB DETAILS

SKILLS

Access Control, Agile Programming Methodologies, Amazon Web Services (AWS), Apache Spark, Artificial Intelligence (AI), Bank Management, Best Practices, Business Intelligence, Cataloguing, Cloud Computing, Communication Skills, Computer Science, Consulting, Cross-Functional, Cryptography, Data Management, Data Modeling, Data Processing, Data Quality, Data Sets, Data Warehousing, DataArchitect Data Modeling Tool, Database Extract Transform and Load (ETL), Ecosystems, Enterprise Architecture, Enterprise Protection, Financial Compliance, Financial Risk Management, Financial Services, GCP (Good Clinical Practices), Government Organizations, Investment Management, Maintain Compliance, Master Data Management (MDM), Metadata, Microsoft Windows Azure, Operational Audit, Operational Support, Oracle, Python Programming/Scripting Language, Realtime Operating System, Regulatory Compliance, Regulatory Reports, SQL (Structured Query Language), Scalable System Development, Security Compliance, Snowflake Schema, Source Code/Configuration Management (SCM), Structured Data, Systems Engineering, Team Player, Unstructured Data, Wealth Management

LOCATION

NULL, NJ

POSTED

4 days ago

Job Title: Data Architect / Data Modeler

Location: Jersey City, NJ
Position Type: Contract to Hire
Duration: 08/03/2026 08/20/2027

Job Summary

We are seeking an experienced Data Architect / Data Modeler with strong expertise in Enterprise Data Architecture, Data Modeling, and Modern Data Engineering to support large-scale enterprise data initiatives within the Financial Services domain.

The ideal candidate will have extensive experience designing scalable cloud-based data platforms, building enterprise data models, and implementing modern data architecture solutions across complex enterprise environments. This role requires hands-on experience with cloud-native technologies, ETL/ELT frameworks, distributed data processing, and enterprise governance practices.

The candidate will work closely with business stakeholders, enterprise architecture teams, data governance organizations, and analytics teams to deliver secure, scalable, and high-performing enterprise data solutions aligned with regulatory and compliance requirements.

Key Responsibilities

Design and implement enterprise-wide data architecture solutions for large-scale financial services environments.
Develop conceptual, logical, and physical data models supporting operational, analytical, and reporting platforms.
Architect and support modern cloud-native data platforms including data lakes, data warehouses, and lakehouse ecosystems.
Build and maintain scalable ETL/ELT pipelines, data ingestion frameworks, and transformation processes.
Design and implement batch and real-time data integration solutions for structured and semi-structured datasets.
Support Master Data Management (MDM) initiatives across client, account, security, and reference data domains.
Collaborate with enterprise architecture, governance, compliance, and security teams to establish enterprise data standards and best practices.
Implement data governance, metadata management, lineage tracking, and data quality frameworks.
Optimize enterprise data platforms for scalability, performance, reliability, and cost efficiency.
Support regulatory reporting, audit, compliance, and risk management initiatives within financial services environments.
Participate in cloud migration and modernization programs involving legacy and distributed data platforms.
Enable enterprise analytics, AI/ML, reporting, and business intelligence capabilities through governed and trusted data solutions.

Required Skills & Experience

8 10 years of experience in Enterprise Data Architecture and Data Modeling.
Strong hands-on experience in Data Engineering and modern data pipeline development.
Expertise with cloud-based data platforms such as Snowflake, Databricks, or similar technologies.
Strong understanding of Data Warehouses, Data Lakes, and Lakehouse architectures.
Experience with legacy/on-prem data platforms such as Oracle Exadata.
Hands-on experience designing ETL/ELT frameworks using Spark-based pipelines, Snowflake Tasks & Streams, or similar technologies.
Strong experience with structured and unstructured data ingestion and integration patterns.
Experience supporting enterprise modernization and legacy transformation initiatives.
Hands-on experience with Master Data Management (MDM) and enterprise data governance frameworks.
Strong understanding of metadata management, data lineage, data cataloging, and data quality processes.
Experience working within financial services and compliance-driven data environments.
Advanced SQL expertise along with programming experience in Python, PySpark, or Snowpark.
Experience with dbt (Data Build Tool) for:
- Data transformation and modeling
- ELT pipeline development
- Modular and reusable SQL workflows
- Data testing and documentation
- Version control integration
Experience with cloud platforms such as Azure, AWS, or GCP and their integration with Snowflake and Databricks.
Familiarity with Kafka, Spark Streaming, event-driven architectures, and real-time data processing frameworks.
Strong understanding of enterprise security, governance, encryption, masking, and role-based access control mechanisms.
Experience working within Agile delivery environments and collaborating with cross-functional teams.

Preferred Qualifications

Experience supporting enterprise cloud modernization initiatives.
Exposure to large-scale distributed data platforms and real-time analytics environments.
Knowledge of enterprise architecture and governance frameworks.
Strong communication and stakeholder management skills.
Financial Services, Banking, Investment Management, or Wealth Management domain experience preferred.

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.

About the Company

Argyllinfotech

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