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Data Architect - AWS & Databricks

K-Tek Resourcing LLCUnited States🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationUnited States
AWSDatabricksUnityDelta Lake

Job description

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.

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