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Location: Tustin, CA Salary: $200,000.00 USD Annually - $220,000.00 USD Annually Description:
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 Google Cloud Platform.
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
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