Senior Data Platform Architect & Transformation Leader

Centraprise, Corp.; Irvine (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

Centraprise, Corp. is seeking a Consulting Partner - Data Engineering & Modern Data Platforms in Irvine, CA. This senior, hands-on leadership role blends executive consulting with deep architecture and engineering expertise to drive large-scale data transformations.

You will lead modernization programs across data ingestion, transformation, storage, and governance, partnering with engineers and executives to design scalable lakehouse architectures using Databricks, Spark, SQL and dbt.

Qualifications

• 15+ years of experience in data engineering, data platforms, analytics, or technology architecture.
• 10+ years of hands-on data engineering and data platform tech experience.
• Experience architecting enterprise-scale data platforms.
• Hands-on with Spark/PySpark and SQL.
• Experience with cloud data platforms (Databricks or Snowflake).
• Experience with dbt and Airflow.

Responsibilities

• Serve as senior technical advisor for complex data platform transformations.
• Define data platform architectures including lakehouse, ingestion, storage, governance and security.
• Lead modernization strategies for legacy and cloud data ecosystems.
• Review architecture decisions and establish standards and reference architectures.
• Provide hands-on guidance and resolve critical engineering issues.
• Lead large-scale data modernization programs and coordinate cross-team delivery.

Skills

Data engineering

Spark/PySpark

SQL

Cloud data platforms

dbt

Airflow

Executive engagement

Architecture leadership

Tools

Databricks

Snowflake

Spark

PySpark

dbt

Airflow

Job description

Centraprise, Corp. is seeking a Consulting Partner - Data Engineering & Modern Data Platforms in Irvine, CA. This senior, hands-on leadership role blends executive consulting with deep architecture and engineering expertise to drive large-scale data transformations.

You will lead modernization programs across data ingestion, transformation, storage, and governance, partnering with engineers and executives to design scalable lakehouse architectures using Databricks, Spark, SQL and dbt.