Enterprise Data Architect
8 days ago
Dallas
Job DescriptionRole: Enterprise Data Architect Location: Dallas, Pittsburgh, Cleveland Experience: 12+ years Duration: Full time We are seeking an Enterprise Data Consultant to support the design, delivery, and optimization of large-scale data engineering, analytics, and AI-enabled solutions across the enterprise.This role partners closely with business, technology, and architecture teams to translate complex data requirements into scalable, secure, and compliant solutions.Key Responsibilities:Enterprise Data Analysis & Solution Delivery • Partner with business and technology stakeholders to analyze enterprise data requirements and translate them into scalable data engineering and analytics solutions., • Design, build, and support end-to-end data pipelines, including data ingestion, preprocessing, normalization, transformation, quality checks, and loading across complex data ecosystems., • Lead and contribute to ETL/ELT development using technologies such as Spark, Hadoop, Hive, Kafka, Python, and Scala, ensuring performance, reliability, and data accuracy.Data Platforms & Architecture, • Work with distributed data platforms including HDFS, HBase, Sqoop, Flume, and MapReduce, supporting both batch and real-time processing use cases., • Apply strong data modeling and data design principles to support analytics, reporting, regulatory, and operational needs., • Collaborate with enterprise architects on logical and physical data models aligned with PNC standards.Data Quality, Governance & Compliance, • Support and implement data quality frameworks, including profiling, validation rules, reconciliation, and monitoring to ensure trusted and compliant data., • Collaborate with cross-functional teams to ensure solutions align with enterprise architecture, security, governance, and regulatory requirements.Cloud, Analytics & AI Enablement, • Contribute to cloud-based data solutions, particularly on AWS, supporting data processing, analytics, and ML workloads., • Collaborate with data scientists and ML engineers to enable machine learning and AI use cases, including feature engineering, data preparation, and pipeline integration., • Support development and deployment of ML and AI systems, including exposure to LLM-based solutions, feature stores, and ML lifecycle management tools.MLOps & Agile Delivery, • Participate in or support MLOps practices, including model deployment, monitoring, retraining pipelines, and integration with platforms such as SageMaker, MLflow, Kubeflow, or similar tools., • Work in Agile delivery environments, actively participating in sprint planning, stand-ups, reviews, and retrospectives using tools such as Jira.Stakeholder Engagement & Consulting, • Serve as a client-facing consultant, coordinating across the SDLC and communicating technical concepts clearly to both technical and non-technical stakeholders., • Contribute to solutioning, estimations, POCs, and client proposals, helping shape data, analytics, and AI modernization initiatives.People & Capability Development, • Mentor junior team members, support onboarding, and promote best practices in data engineering, analytics, and platform design., • Foster collaboration across teams to support continuous improvement and delivery excellence.Qualifications & Experience, • 12+ years of experience in data engineering, data analytics, or enterprise data consulting., • Strong hands-on experience with big data and distributed data platforms., • Proficiency in Python, with experience in streaming and real-time data processing., • Solid understanding of data modeling, ETL/ELT design, and data quality practices., • Experience supporting cloud-based data platforms, preferably AWS., • Exposure to machine learning, AI, and MLOps concepts preferred., • Experience working in Agile/Scrum environments., • Strong communication and consulting skills with experience working in client-facing roles., • Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or related field.