Senior Architect: Data Engineering, Cloud Architecture & AI

LaunchCode•Saint Louis, MO

33d•$160,000 - $180,000•Remote

About The Position

As a Senior Architect, your primary responsibility will be to ensure customer success for our Company Partner. This role is dedicated to customer data strategy and advisory delivery. You will be asked to collaborate with company team members to deliver client data strategy engagements incorporating people, process, technology, and data to build a strategic roadmap designed to enable client digital transformation by implementing a strong data management foundation to support tactical technology projects and drive sustainable and scalable business value. You will need to be entrepreneurial, enterprising, and personable, possessing strong leadership qualities, that allow you to play a substantive role in the Data Practice with an ability to scale over time. Senior Architects are skilled at identifying, collaborating, and designing technical solutions for the lifecycle of data - from applications, to reporting, to analytics, to long term storage and retrieval, using Azure technologies and supporting the movement of data across gathering, landing, consuming, and analyzing data across the Azure platform, including SQL Server, Azure Data Factory, Synapse, Data Lake, Cosmos DB, Power BI, Databricks and related technologies. The ideal candidate will have experience in customer-facing roles and had success leading technical and economic value discussions with senior customer executives, including C-suite, that drive key decisions and implementation.

Requirements

Bachelor's or Master's Degree desired in Computer Science, Information Technology, or related field or equivalent experience
8+ years of experience in data engineering, including 4+ years of experience architecting data solutions on Azure
You can apply technical knowledge and insights to create a data modernization roadmap and architect solutions to meet business and IT needs
Deep expertise in Microsoft Azure with experience with Databricks and/or Fabric
Proven ability to design and implement modern data architectures (data lakes, data warehouses, lakehouses, data mesh, streaming pipelines).
Proficiency in Python, PySpark, SQL, and data engineering frameworks.
Azure DevOps (including building Stories and tasks, and using pipelines and ARM templates for publishing code)
Knowledge of infrastructure as code, APIs, security, compliance, and master data management
Demonstrated ability to drive AI strategy and adoption, skilled at balancing AI innovation with responsible AI principles.
Experience optimizing data pipelines, queries, and architectures for performance and cost.
You're results oriented and have a reputation for getting things done
You have a growth mindset and have a deep desire to continue to improve your skills
You're comfortable in fast paced environments
You're confident presenting in front of senior level clients
You have a strong sense of responsibility for a project's success
You thrive in a team environment
You have strong communication skills

Responsibilities

Design Azure based technical solutions leveraging a broad range of the available toolsets with considerations around functionality and performance.
Act as team lead on projects and direct the technology process as well as manage client relationships and expectations to build trust and creditability.
Implement end-to-end data platform solutions for our clients.
Manage client expectations with regard to scope, cost, and timeline.
Actively support solution architects and sales directors in pre-sales activities to drive additional business for our Company Partner.
Author high quality project documentation and other project artifacts, including written case studies detailing use cases and project specifics
Be an effective technical mentor to more junior level teammates.
Deliver complex projects on-time and within budget, proactively identifying and mitigating gaps and risks.
Be an advocate for our Company Partner's Data methodology, leading by example in following best practices and standards.
Expand your knowledge in multiple tools and technologies.
Foster a problem-solving culture that resolves issues through collaboration and partnerships with other parts of the organization.
Support internal Company Partner objectives that help advance data services design and techniques.