Senior Architect- Data Engineering (1148350)

The Judge Group; Tustin (CA); On-site; USD 200,000 - 220,000; Full time

Job summary

The Judge Group seeks a Senior Architect - Data Engineering in Irvine, CA to design and scale our enterprise data platform. You will define blueprints for the data estate, leveraging Databricks, dbt, and Airflow while ensuring scalable, resilient pipelines and cost effectiveness.

You will lead architecture discussions with product, data science, and business leaders, mentor engineers, and drive DataOps maturity through CI/CD and IaC practices.

Qualifications

• 15+ years of experience in data engineering and related fields.
• 10+ years architecting production environments in the modern data stack.
• 4+ years leading architecture and platform initiatives in data engineering.

Responsibilities

• Design end-to-end lakehouse architectures on Databricks with Delta Lake and Unity Catalog.
• Establish robust governance, schema evolution, and data security patterns.
• Develop standard data modeling frameworks (Kimball, Data Vault 2.0) and optimize cost/performance.
• Architect modular, reusable transformation frameworks with dbt; integrate with Databricks.

Skills

Databricks

dbt

Airflow

PySpark

SQL

Delta Lake

Unity Catalog

Data Governance

DataOps

CI/CD

Tools

GitHub Actions

GitLab CI

Azure DevOps

Terraform

Databricks Asset Bundles (DABs)

Job description

Location: Tustin, CA

Salary: $200,000.00 USD Annually - $220,000.00 USD Annually

Senior Architect- Data Engineering

Irvine, CA

Fulltime

Role Overview

We are seeking a visionary and hands-on Senior Data Engineering Architect to design, scale, and optimize our enterprise data platform. In this role, you will define the blueprints for our data estate, leveraging a modern stack centered on Databricks, dbt, and Apache Airflow. You will bridge the gap between complex business strategy and technical implementation, ensuring our data pipelines are scalable, resilient, and cost-effective.

Key Responsibilities

Architecture & Platform Design

• Design end-to-end lakehouse architectures on Databricks utilizing Delta Lake and Unity Catalog.
• Establish robust governance, schema evolution, and fine-grained data security patterns.
• Formulate standard frameworks for data modeling (e.g., Kimball dimensional modeling, Data Vault 2.0).
• Optimize infrastructure for optimal price-to-performance across batch and streaming workloads.

Data Pipeline & Orchestration Engineering

• Architect modular, reusable transformation frameworks using dbt Core/Cloud integrated with Databricks.
• Standardize data processing patterns using PySpark, Delta Live Tables (DLT), and Spark SQL.
• Build highly observable, dynamic orchestration workflows using Apache Airflow.
• Design cross-DAG dependency models, custom providers, and robust error-handling mechanisms.

DataOps & Engineering Excellence

• Drive DataOps maturity by implementing CI/CD pipelines via GitHub Actions, GitLab CI, or Azure DevOps.
• Deploy infrastructure-as-code patterns using Terraform and Databricks Asset Bundles (DABs).
• Embed automated data quality testing directly into the dbt and Airflow lifecycle.
• Define service-level indicators (SLIs) and objectives (SLOs) for pipeline uptime and data freshness.

Leadership & Stakeholder Management

• Serve as the principal technical authority and escalation point for data engineering teams.
• Mentor senior and mid-level data engineers through code reviews and architectural workshops.
• Collaborate with product managers, data scientists, and business leaders to solve data gaps.

Required Qualifications

• Overall 15+ Years of experience
• 10+ years of total experience in data engineering, data warehousing, and distributed systems.
• 4+ years of dedicated experience architecting production environments within the modern data stack.

Technical Proficiencies

• Databricks: Advanced mastery of Photon engine, Unity Catalog, Delta Lake optimization (Z-order, Liquid Clustering), and DLT.
• dbt: Expert-level proficiency with compl ex macro development, custom materializations, and multi-project dbt mesh architectures.
• Airflow: Deep understanding of Airflow scheduling, custom operators, dynamic task mapping, and infrastructure scaling.
• Languages: Elite proficiency in Python (PySpark) and advanced SQL.
• Cloud Infrastructure: Strong experience with at least one major cloud ecosystem provider: AWS, Azure, or GCP.

Soft Skills

• Strong technical communication skills to distill complex infrastructure designs for non-technical stakeholders.
• Natural ability to lead by influence and drive cross-functional engineering initiatives.

Preferred Qualifications

• Official Databricks certifications (e.g., Databricks Certified Data Engineer Professional or Solutions Architect).
• Active contributor to open-source data communities (dbt, Airflow, or Apache Spark).
• Solid foundation in streaming data technologies like Apache Kafka or AWS.