> Markdown version of [/jobs/ext/1183790-data-architect-modeler](https://www.wearedevelopers.com/jobs/ext/1183790-data-architect-modeler). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Architect/Modeler - **Company:** Save Mart Supermarkets LLC - **Location:** Jersey City, NJ, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Information Systems, Computer Programming, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Masking, Data Transformation, Data Warehousing, Database Queries, Distributed Computing Environment, Distributed Data Store, Oracle Exadata, Python (Programming Language), Meta-Data Management, Role-Based Access Control, Reference Data, Cloud Services, Enterprise Data Management, Cloud Platform System, Data Ingestion, Snowflake, Data Build Tool (dbt), Apache Spark, Event Driven Architecture, Data Lakes, Pyspark, Semi-structured Data, Information Technology, Data Lineage, Real Time Data, Apache Kafka, Spark Streaming, Data Management, Tools for Reporting, Physical Data Models, Cloud Migration, Stream Analytics, Software Version Control, Data Pipelines, Api Management, Databricks - **Published:** July 4, 2026 - **Apply:** https://www.careerjet.com/jobad/usb01807d25d77315097620cd843b171b0 ## About the Role 8 10 years of experience in Enterprise Data Architecture and Data Modeling across modern data platforms. Hands-on experience with Data Engineering and development of scalable enterprise data pipelines. Strong expertise in cloud-based data platforms such as Snowflake, Databricks, and distributed data processing technologies. Experience with on-premise data platforms and legacy data warehouses such as Oracle Exadata. Strong understanding of data warehouse, data lake, and lakehouse architectures. Experience designing and implementing ETL/ELT frameworks using Spark, Snowflake Tasks, Streams, or similar technologies. Expertise in Master Data Management (MDM), enterprise data governance, metadata management, data lineage, and data quality. Strong SQL skills with programming experience in Python, PySpark, or Snowpark. Experience with dbt (Data Build Tool) for data transformation, modeling, ELT development, testing, documentation, and version control. Experience with Azure, AWS, or GCP and integration with Snowflake and Databricks. Familiarity with API integrations, Kafka, Spark Streaming, and event-driven architectures. Understanding of enterprise security, compliance, RBAC, data masking, and encryption. Experience working in Agile environments and collaborating with cross-functional teams. Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field., Knowledge of enterprise architecture and data governance frameworks. Financial Services, Investment Management, or Wealth Management industry experience. Excellent communication, collaboration, and stakeholder management skills. ## Description We are seeking an experienced Data Architect with strong Data Modeling expertise and hands-on Data Engineering capabilities to support enterprise data initiatives within the Financial Services industry. The ideal candidate will design scalable cloud-based data platforms, develop enterprise data models, and deliver modern data architecture solutions that support analytics, reporting, regulatory compliance, and business intelligence initiatives. 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 cloud-native data platforms including enterprise data lake, warehouse, and lakehouse ecosystems. Develop ETL/ELT pipelines, data ingestion frameworks, and transformation processes. Design scalable batch and real-time data integration solutions for structured and semi-structured data. Support Master Data Management (MDM) initiatives across security, account, client, and reference data domains. Collaborate with enterprise architecture, governance, security, compliance, and business teams to establish enterprise data standards. Implement metadata management, data lineage, governance, and data quality frameworks. Optimize enterprise data platforms for scalability, reliability, performance, and cost efficiency. Support regulatory, audit, risk, and compliance reporting requirements. Participate in cloud migration and modernization initiatives involving legacy and distributed data systems. Enable analytics, AI/ML, reporting, and business intelligence capabilities through trusted enterprise data solutions. Preferred Skills Experience supporting enterprise modernization and cloud transformation initiatives. Exposure to real-time analytics and distributed data platforms. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)