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# Data Architect

- **Company:** Syrencloud Llc
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Batch Processing, Business Intelligence Development, Communications Protocols, Computer Programming, Data Architecture, Data Discovery, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Dataspaces, Data Systems, Database Design, DeviceNet, Disaster Recovery, File Systems, Python (Programming Language), PostgreSQL, Meta-Data Management, MongoDB, SAP ERP, Performance Tuning, SQL Databases, Data Streaming, Systems Integration, TCP/IP, Digital Twin, Enterprise Software Applications, Data Storage Technologies, Warehouse Management Systems, Data Ingestion, Azure Data Factory, Snowflake, Apache Spark, Generative AI, HybridCloud, Microsoft Fabric, Data Lakes, Pyspark, Data Lineage, Data Analytics, SAP S/4HANA, Apache Kafka, Data Management, Physical Data Models, Multiaccess Edge Computing, Virtual Agents, Databricks, Microservices
- **Published:** June 24, 2026
- **Apply:** https://www.dice.com/job-detail/102d6624-2be7-4e70-bb99-a9ef2250e996

## About the Role

* 10+ years of overall experience with at least 5+ years in Data Architecture for enterprise-scale environments.
 * Strong background as a Data Engineer with hands-on experience before transitioning into Architecture.
 * Expert-level experience with Databricks (mandatory).
 * Strong proficiency in Snowflake architecture and implementation.
 * Experience working with Generative AI or AI-enabled data platforms.
 * Strong understanding of Manufacturing and Supply Chain business processes and data ecosystems.
 * Extensive experience working with SAP S/4HANA, SAP ECC, and integrating multiple enterprise data sources.
 * Strong expertise in:

 * Data Modeling
 * Data Discovery & Curation
 * Database Design
 * Logical & Physical Data Architecture

Experience designing solutions across Azure (preferred) and hybrid cloud/on-premises environments, including disaster recovery, performance tuning, and cost optimization.

Hands-on experience with streaming and batch processing technologies such as:

 * Apache Spark / PySpark
 * Kafka
 * Azure Event Hub
 * Azure IoT Hub
 * Azure Data Factory
 * Similar modern data integration technologies

Experience working with data storage and serving technologies such as:

 * Snowflake
 * Databricks Delta Lake
 * File Storage/Data Lake
 * MongoDB
 * PostgreSQL
 * Other modern data platforms

Strong programming skills in SQL and Python.

Familiarity with industrial communication protocols and edge computing concepts, including TCP/IP, HTTPS, HART, DeviceNet, and related technologies.

Excellent communication and stakeholder management skills with the ability to collaborate across executive leadership, factory operations, IT, analytics, and engineering teams.
__________________________________________________

Preferred Skills

 * Experience with Microsoft Fabric and its data engineering and analytics capabilities.
 * Knowledge of modern architectural paradigms such as:

 * Data Mesh
 * Data Fabric
 * Lakehouse Architecture

Experience building data platforms for AI/ML and Generative AI workloads.

Experience with microservices-based industrial analytics architectures or digital twin initiatives.

Exposure to Pharmaceutical/Life Sciences clients and regulated industry data environments.

Relevant certifications such as:

 * Databricks
 * Snowflake
 * Azure Data Architect
 * DAMA CDMP, * A hands-on Data Architect with a strong engineering mindset.
 * Proven experience designing enterprise-scale data platforms for Manufacturing and Supply Chain organizations.
 * Expert in Databricks and proficient in Snowflake, with experience integrating complex enterprise systems such as SAP S/4HANA and SAP ECC.
 * Passionate about modern data architecture, cloud platforms, and Gen AI-enabled data solutions.
 * Strong leadership, communication, and stakeholder management skills with the ability to drive enterprise data transformation initiatives.

## Description

We are seeking an experienced Data Architect with a strong Data Engineering foundation to design and govern a scalable, enterprise-grade data architecture that enables insights from factory-floor systems to enterprise analytics and AI-driven applications. The ideal candidate will define a future-ready data ecosystem that simplifies complex data landscapes, supports real-time and batch processing, and aligns with long-term business strategy.

This role requires expertise in Databricks, Snowflake, Microsoft Fabric, and modern cloud data platforms, along with deep experience in Manufacturing and Supply Chain domains.

Note: Candidates should have started their careers as Data Engineers and evolved into Architecture roles. Profiles primarily focused on BI Development or Data Analytics will not be considered., * Define and own the end-to-end enterprise data architecture strategy, including data ingestion, integration (edge-to-cloud), storage, processing, governance, and consumption layers.

 * Design scalable architectures for high-volume, high-velocity real-time, streaming, and batch data originating from IoT devices, factory equipment, sensors, warehouses, and enterprise applications.
 * Architect modern Lakehouse solutions using Databricks and Snowflake to support enterprise analytics, AI/ML, and Generative AI initiatives.
 * Develop conceptual, logical, and physical data models along with canonical data models, golden-record strategies, and metadata frameworks for manufacturing and supply chain entities.
 * Design and implement data integration strategies across multiple enterprise systems, including:

 * SAP S/4HANA
 * SAP ECC
 * Other ERP, MES, WMS, CRM, and enterprise applications

Establish and govern enterprise data standards, including:

 * Data Governance
 * Metadata Management
 * Data Lineage & Traceability
 * Master Data Management (MDM)
 * Data Quality Frameworks
 * Security and Compliance

Evaluate and recommend modern cloud and hybrid data technologies while optimizing for scalability, reliability, performance, and cost.

Collaborate with business stakeholders, engineering teams, manufacturing SMEs, and leadership to translate business requirements into scalable architectural solutions.

Lead architecture implementation across projects, mentor engineering teams, and drive adoption of best practices and continuous improvement.

Enable enterprise Generative AI and advanced analytics use cases by building a robust and trusted data foundation.


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