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Data Architect

1 month ago

Detroit, United States PDSSOFT Full time

Title:

Data Architect Location:

Detroit, MI (Relocation Available) Industry : Retail Salary:

$170k + Bonus & Benefits Overview We have partnered with a global organization searching for a Data Architect to join their growing team. As the Data Architect your primary responsibility will be to ensure building a scalable, secure, and efficient data platform/ Lakehouse with Azure / Databricks. The Cloud Data Solutions Architect will collaborate with Digital, AI, and ML Architects and teams to define data activation frameworks. The role is a senior level technical role that will be accountable for the end-to-end cloud data management solution. The ideal candidate will have experience in large scale modern data warehouse development and had success leading cross-team technical discussions that drive key decisions and implementation. Data Engineering Lead – Responsibilities Oversight and execution of the data engineering roadmaps. Set up Dev Ops and CICD processes for data engineering. Could be hands-on in the architecture design and building team engineering best practices. Manage project priorities and product deliveries. Drive technical initiatives from execution toward delivery. Business and tech planning for various company and project initiatives Collaborate with architects for data architecture design. You will have the opportunity to build and Lead the Data Engineering Global team sitting across North American, India GCC and European offices. Act as a coach, mentor, and leader for the Data Engineering team. Ensuring development, engagement, and workflow management. Collaboration with key business and technical stakeholders. Manage various budgets/costs associated with projects and team initiatives. Requirements Extensive experience with multiple full life-cycle data warehouse and transformation projects in public cloud environments Skilled in creating efficient architectures that optimize cost and performance, meeting both functional and SLA requirements. Deep knowledge of data architectures, including Data Lakehouse and Data Mesh models Proficient in developing solutions using No-SQL data platforms. Familiar with Docker and orchestration tools such as Docker Compose or Kubernetes Strong SQL and database expertise, capable of handling large structured and unstructured data sets Well-versed in enterprise reporting solutions like PowerBI, Qlik, and Tableau, as well as data virtualization and semantic modelling Excellent written and verbal communication skills to convey key decisions, recommendations, and technical concepts to both technical and non-technical audiences.

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