Data Architect-68464

Hitachi•Reading, PA

About The Position

Join our Data & Analytics organization, where we design and modernize enterprise-scale data platforms that power business intelligence, advanced analytics, AI/ML, and enterprise reporting. You will collaborate with business stakeholders, product managers, solution architects, data engineers, and AI/ML teams to establish scalable data architectures and modern cloud-based data ecosystems. The team focuses on building secure, reliable, high-performance data platforms using modern cloud, Lakehouse, streaming, and data engineering technologies.

Requirements

10+ years of experience across data architecture, data engineering, or enterprise data platform development.
5+ years leading data engineering initiatives and delivering enterprise-scale data solutions.
Proven experience designing and owning enterprise data architecture , not just developing individual pipelines.
Bachelor's degree in Computer Science, Information Systems, Engineering, or related discipline.
Strong expertise in conceptual, logical, and physical data modeling.
Deep knowledge of data warehousing, ETL/ELT, Data Lakes, and Lakehouse architectures.
Experience designing distributed, scalable, high-performance data platforms.
Strong understanding of batch, streaming, and event-driven data processing.
Strong experience with AWS.
Experience with AWS data services including S3, EMR, Glue, and Redshift.
Strong experience with Snowflake or comparable modern cloud data platforms.
Hands-on/architecture experience with: Spark | Kafka | Airflow | Talend | dbt | Python | SQL
Experience across relational and NoSQL platforms such as: SQL Server | PostgreSQL | Amazon Aurora | DynamoDB
Strong understanding of: Data Lake/Lakehouse | Event-Driven Architecture | Microservices | REST APIs | Data Modeling
Experience with: Kubernetes | Docker | Git | CI/CD | Infrastructure as Code
Strong understanding of Agile delivery, DevOps, automation, monitoring, and operational best practices is expected.

Responsibilities

Define and maintain enterprise data architecture , including conceptual, logical, and physical data models.
Architect scalable cloud data platforms, data warehouses, data lakes, and lakehouse solutions.
Lead architecture and implementation of ETL/ELT, batch processing, streaming, and real-time data integration solutions.
Design enterprise data solutions supporting BI, analytics, AI/ML, and reporting initiatives.
Partner with business stakeholders, product managers, architects, and engineering teams to translate business requirements into scalable technical architectures.
Establish architecture patterns and standards for data ingestion, transformation, storage, processing, integration, and consumption.
Design distributed, scalable, highly available, and high-performance data architectures.
Ensure data platforms meet requirements for performance, reliability, security, monitoring, automation, and availability.
Provide technical leadership to data engineering teams and guide implementation of enterprise data solutions.
Support event-driven architectures, APIs, microservices, and modern data integration patterns.
Drive engineering best practices across Agile, CI/CD, DevOps, containerization, and Infrastructure as Code.
Evaluate emerging technologies and recommend platforms, tools, and architecture improvements to modernize the enterprise data ecosystem.
Collaborate with AI/ML and analytics teams to enable data consumption for advanced analytics and AI use cases.