3025 Data Cloud Software Engineer jobs in Dallas,TX

15+ years of IT experience with 8+ years in architecture leadership roles
Proven experience leading cloud transformation and legacy modernization programs at enterprise scale
Brings broad cross-domain knowledge spanning enterprise and solution architecture, data platforms, integration, infrastructure, networking, and security to design scalable, secure, and resilient enterprise solutions.
Experience working within an Enterprise Architecture framework (e.g., TOGAF).
Fluency in modern architecture practices, including cloud-native, microservices, event-driven, and AI-enabled architectures.
Proven experience leading legacy modernization and enterprise cloud transformation initiatives across complex technology landscapes.
Ability to define and govern enterprise architecture standards, patterns, reference architectures, and technology roadmaps aligned with business strategy.
Expertise in creating architecture artifacts and diagrams (e.g., Visio, draw.io).
Collaborate with business leaders, IT leadership, and engineering organizations to translate strategic objectives into scalable technology solutions.
Experience in risk management and executive-level presentations.
Knowledge of FinOps and Cloud cost optimization strategies
Demonstrated ability to lead across organizational boundaries and drive consensus.

Sr. Data Engineer

McKesson

Irving, TX 75039

Bachelor's Degree in Computer Science or related field of study
Five (5) years of experience in the job offered or a related occupation
Experience in data engineering with Databricks and AWS
Experience with Apache Spark, SQL, and Python or Scala
Experience with Delta Lake, Unity Catalog, and cloud data warehouses (e.g., Redshift)
Experience with data modeling, ETL/ELT processes, and data governance
Experience with orchestration tools including Gitlab or Bitbucket and CI/CD practices
Experience in collaborating with cross-functional teams to deliver data solutions using Python and Databricks in Agile environments
Experience with design and optimizing scalable data pipelines with Python and Spark in Databricks
Experience with developing modular, reusable components in Databricks notebooks and workflows
Experience in implementing data validation frameworks to ensure pipeline accuracy and consistency