Senior Architect-Data Engineer

Tata Consultancy Services; Irvine (CA); On-site; USD 150,000 - 240,000; Full time

Job summary

Tata Consultancy Services in Irvine, CA is seeking a Senior Architect – Data Engineering to design, scale, and optimize an enterprise data platform built on Databricks, dbt, and Airflow. You will define blueprints for the data estate, ensure scalable pipelines, and drive governance and cost efficiency.

You will lead data engineers, mentor senior staff, and collaborate with product managers, data scientists, and business leaders to implement end-to-end lakehouse architectures and robust DataOps

Qualifications

• 15+ years overall experience in IT with data engineering focus.
• 10+ years in data warehousing and distributed systems.
• 4+ years architecting production environments in the modern data stack.

Responsibilities

• Design end-to-end lakehouse architectures on Databricks; leverage Delta Lake and Unity Catalog.
• Define blueprints for data estate governance, schema evolution and data security.
• Mentor senior and mid-level data engineers; lead architecture workshops.
• Collaborate with product managers, data scientists, and business leaders to solve data gaps.

Skills

Python (PySpark)

SQL

Technical communication

Leadership

Cross-functional collaboration

Cloud platforms

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

dbt

Airflow

Terraform

Job description

Job Description

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