Senior Data Architect

Tredence Inc.; United States; On-site; USD 140,000 - 210,000; Full time

Job summary

Tredence Inc. in the United States is seeking a Data Architect to own the design and delivery of modern data platforms built on AWS and Databricks. You will lead hands-on engineering while guiding a team through ingestion, transformation, and warehousing of structured and unstructured data.

You will partner with architects and stakeholders to translate requirements into robust, scalable designs, establish data quality and governance standards, and drive high-impact data solutions in production.

Qualifications

• Hands-on AWS services in production environments for compute, storage, orchestration and security.
• Deep Databricks expertise including Delta Lake, Unity Catalog, cluster management and job orchestration.
• Proven ability to design and operate ingestion, transformation and warehousing pipelines across structured and unstructured data.
• Experience leading and mentoring data engineering teams, managing delivery timelines and quality.

Responsibilities

• Architect and deliver end-to-end data engineering solutions on AWS and Databricks.
• Design scalable pipelines for structured and unstructured data.
• Lead and mentor a team of data engineers, overseeing sprint planning, code quality, and delivery.
• Partner with architects and stakeholders to translate requirements into production-ready designs.
• Establish and maintain data quality, governance, and platform scalability.

Skills

AWS Services

Databricks Platform

Data Engineering Lifecycle

Team Leadership

Job description

AWS + Databricks Ecosystem | Data Engineering Leadership | Full-Time

ROLE OVERVIEW

We are looking for a Data Architect to own the design and delivery of modern data platforms built on AWS and Databricks. This role combines deep hands-on engineering with team leadership, covering data ingestion, transformation, and warehousing across structured and unstructured sources.

KEY RESPONSIBILITIES

• Architect and deliver end-to-end data engineering solutions on AWS and Databricks, spanning ingestion, transformation, and warehousing layers.
• Design scalable pipelines for structured and unstructured data, balancing reliability, performance, and cost efficiency.
• Lead and mentor a team of data engineers, overseeing sprint planning, code quality, and technical delivery.
• Partner with architects and business stakeholders to translate requirements into robust, production-ready designs.
• Establish and maintain standards for data quality, governance, and platform scalability.

WHAT WE'RE LOOKING FOR

MUST-HAVE SKILLS

• AWS Services — Hands-on expertise across core AWS services spanning compute, storage, orchestration, and security in production environments.
• Databricks Platform — Deep proficiency in Databricks, including Delta Lake, Unity Catalog, cluster management, and job orchestration at scale.
• Data Engineering Lifecycle — Proven ability to design and operate ingestion, transformation, and warehousing pipelines across structured and unstructured data.
• Team Leadership — Experience leading and mentoring data engineering teams, managing delivery timelines, and driving technical quality.

GOOD-TO-HAVE SKILLS

• Agentic AI Exposure — Working understanding of agentic AI concepts and frameworks, and how they apply within modern data platforms.
• Manufacturing Industry Knowledge — Familiarity with manufacturing industry data landscapes, processes, and common use cases.
• Data Modelling — Understanding of data modelling principles, including dimensional and canonical modelling approaches.