Data Architect Sr Principal

FedEx Dataworks•Memphis, TN

3d•$7,937 - $27,827•Remote

About The Position

As a Data Platform Architect, you will be responsible for designing, implementing, and maintaining scalable and efficient data platforms to support the organization's data-driven initiatives. You will collaborate with cross-functional teams to understand business requirements, design data architectures, and implement solutions that enable efficient data processing, storage, and analysis. The role requires a deep understanding of various data technologies, cloud platforms, and data engineering best practices.

Requirements

Proficiency in designing and implementing data architectures using cloud platforms (e.g., AWS, Azure, GCP).
Hands-on experience with big data technologies such as Hadoop, Spark, Kafka, etc.
Ability to lead and perform reverse engineering activities related to existing data flows and design/implement improvements
Solution architecture experience in translating business needs and vision into roadmap, project deliverables, and organizational strategies
Solid understanding of data architecture and data modeling techniques
Consensus building skills to drive alignment across cross-functional teams
Ability to adapt and maintain a positive and professional attitude to deliver scalable, secure, and compliant solutions.
Proven experience designing high-throughput, asynchronous, event-driven data workflows and distributed messaging platforms (e.g., Apache Kafka).
Experience architecting large-scale data solutions in highly regulated industries, with a strong understanding of compliance, governance, and data security requirements. Including but not limited to (GraphDB, Sub-Graphs, No-SQL and RDMS)
Demonstrated ability to lead end-to-end architecture across the full lifecycle, from ideation through delivery, for enterprise-scale platforms spanning multiple applications and complex, heterogeneous data sets.
Experience evaluating emerging and cutting-edge technologies for enterprise applicability, including proof-of-concept development, risk assessment, and build-vs-buy analysis.
Experience architecting AI-first and AI-enabled solutions, including the enabling infrastructure, data pipelines, and integration patterns that support machine learning and generative AI capabilities at enterprise scale.
Ability to produce architecture diagrams and documentation tailored to multiple audiences, from executive-level conceptual views to detailed technical diagrams for engineering teams.
Expertise across a wide range of technologies, including microservices architecture, API design, and DevOps practices.
Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
Demonstrated leadership abilities, with experience mentoring and coaching junior team members.
Proven ability to thrive in a fast-paced, dynamic environment and manage multiple priorities effectively.
Bachelor's degree, in computer science, engineering, information systems and/or equivalent formal training or work experience.
Eight plus (8+) years equivalent work experience in information technology or engineering environment.
Experience as a leader or a senior member of multi-functional project teams.
Excellent interpersonal skills and the ability to communicate effectively to senior audiences.

Nice To Haves

Industry certifications such as TOGAF, AWS Certified Solutions Architect, or Microsoft Certified: Azure Solutions Architect Expert are a plus.
A related advanced degree may offset related experience requirements.

Responsibilities

Lead the design and architecture of innovative data solutions that address the organization's business needs and challenges.
Take a hands-on approach to implementing data solutions, including data integration, data warehousing, ETL processes, and data analytics pipelines (including but not limited to coding).
Collaborate with cross-functional teams, including engineering, product management, and business stakeholders, to develop comprehensive data solution strategies.
Conduct architecture reviews and assessments, and provide recommendations to optimize existing data systems and processes.
Drive continuous improvement initiatives by identifying opportunities for innovation and efficiency in solution delivery.
Mentor and coach junior members of the architecture and data engineering team, providing guidance and support in their professional development.