Senior Architect-Data Engineer - Irvine, CA | TCS Job

Senior Architect – Data Engineering 

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

Salary Range- $150,000-$240,000 a year