Senior Data Architect — Cloud Data Platform & Analytics

hitachi; Pennsylvania; On-site; USD 140,000 - 190,000; Full time

Job summary

Hitachi Digital Services is seeking a Senior Data Architect to design and scale enterprise data platforms and analytics ecosystems. You will collaborate with business stakeholders, product teams, and data engineers to translate complex requirements into robust cloud-based architectures.

You will lead architecture efforts for ETL/ELT pipelines, data lakes, lakehouses, and real-time data integration, while ensuring performance, security, and compliance across the enterprise data stack.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related discipline.
• 10+ years of experience across data architecture, data engineering, or enterprise data platform development.
• Proven experience designing and owning enterprise data architecture beyond pipelines.
• Strong knowledge of data warehousing, ETL/ELT, and Lakehouse architectures.

Responsibilities

• Define and maintain enterprise data architecture across conceptual, logical, and physical models.
• Architect cloud data platforms, data warehouses, data lakes, and lakehouse solutions.
• Lead ETL/ELT, batch, streaming, and real-time data integration initiatives.
• Design data solutions supporting BI, analytics, AI/ML, and reporting.
• Collaborate with stakeholders to translate requirements into scalable architectures.

Skills

10+ years data architecture

Data engineering leadership

Enterprise data platforms

Education

Bachelor's degree in CS/IS/Engineering

Tools

Spark

Kafka

Airflow

Talend

dbt

Python

SQL

Job description

Hitachi Digital Services is seeking a Senior Data Architect to design and scale enterprise data platforms and analytics ecosystems. You will collaborate with business stakeholders, product teams, and data engineers to translate complex requirements into robust cloud-based architectures.

You will lead architecture efforts for ETL/ELT pipelines, data lakes, lakehouses, and real-time data integration, while ensuring performance, security, and compliance across the enterprise data stack.