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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Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: cxjudgpa
- Position Id: 1148350
- Posted 2 days ago
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