Data Engineering, Management & Governance Senior Manager

Accenture•Seattle, WA

18h•Onsite

About The Position

Accenture LLP has multiple openings for the position of Data Engineering, Management & Governance Senior Manager in Seattle, WA. The role involves architecting scalable solutions for new rollouts, enhancements, and lifecycle maintenance, integrating best practices across DevOps, MLOps, and DataOps frameworks. The Senior Manager will lead strategic design and oversight of data system components and enterprise applications, ensuring alignment with organizational goals and long-term technology roadmaps. They will drive cross-functional project planning for complex IT initiatives, defining objectives, technology stacks, systems architecture, schedules, budgets, and staffing strategies in collaboration with senior leadership. The role also includes overseeing application performance and service delivery, ensuring adherence to SLAs and proactively managing scope, budget, and timelines across multiple concurrent projects. Additionally, the Senior Manager will set technical standards and governance for application design and development, ensuring code quality, security, and compliance across engineering teams. They will develop system specifications and establish AI initiatives, MLops and Dataops for complex systems, and identify and solve complex problems that require in-depth evaluation of variable factors for team implementation. The position requires mentoring and leading engineering teams, translating business and system requirements into actionable design specifications, and fostering talent development. The Senior Manager will manage program-level execution, including issue resolution, stakeholder reporting, and budget forecasting, while making strategic decisions in consultation with executive leadership. They will shape strategic direction, prototype innovative solutions, and ensure alignment with client and senior management expectations. Finally, the role involves representing the organization in senior-level engagements, building trust with clients and internal executives through effective communication and relationship management.

Requirements

Bachelor’s degree in Computer Science, Technology, Computer Information Systems, Computer Applications, Engineering, or related field.
7 years of experience (of which 5 years must be progressive post-baccalaureate experience) in the IT consulting industry.
7 years of experience in leading architectural and design decisions and managing ETL projects and providing complex ETL and backend solutions.
7 years of experience in designing, developing and managing large-scale Data warehouse, Data Lake solutions and Data infrastructure across multiple systems following SDLC best practices.
7 years of experience utilizing GitHub for version control, JIRA for task tracking, Jenkins for CI/CD pipeline automation, and Apache Airflow for scheduling and monitoring batch job executions across distributed environments.
7 years of experience coding and deploying applications using DevOps by utilizing GitLab, AWS, and Splunk.
7 years of experience developing and maintaining applications, and extract, transform, and load (ETL) leveraging Scala, Python, PySpark, AWS services, PL/SQL and Unix Shell Scripting to manage complex data workflows, automate processes, and enable reliable communication between enterprise systems and applications.
7 years of experience working with Hive, SQL databases including MySQL, Presto, Amazon DynamoDB, RedShift and visualization using Tableau.
7 years of experience driving delivery orchestration and design decisions suggesting improvements, and managing onshore and offshore teams supporting critical applications.
5 years of experience applying cloud-native development principles and Agile methodology to build scalable, resilient applications while optimizing data ingestion and transformation in the cloud including AWS.
5 years of experience creating prototype solutions, producing, and maintaining data and infrastructure for Machine learning, experimentation, and AI applications.
Willingness and ability to travel domestically approximately 80% of the time to meet client needs.

Responsibilities

Architect scalable solutions for new rollouts, enhancements, and lifecycle maintenance, integrating best practices across DevOps, MLOps, and DataOps frameworks.
Lead strategic design and oversight of data system components and enterprise applications, ensuring alignment with organizational goals and long-term technology roadmaps.
Drive cross-functional project planning for complex IT initiatives, defining objectives, technology stacks, systems architecture, schedules, budgets, and staffing strategies in collaboration with senior leadership.
Oversee application performance and service delivery, ensuring adherence to SLAs and proactively managing scope, budget, and timelines across multiple concurrent projects.
Set technical standards and governance for application design and development, ensuring code quality, security, and compliance across engineering teams.
Develop system specifications and establish AI initiatives, MLops and Dataops for complex systems.
Identify and solve complex problems that require in-depth evaluation of variable factors for team implementation.
Mentor and lead engineering teams, translating business and system requirements into actionable design specifications and fostering talent development.
Manage program-level execution, including issue resolution, stakeholder reporting, and budget forecasting, while making strategic decisions in consultation with executive leadership.
Shape strategic direction, prototype innovative solutions, and ensure alignment with client and senior management expectations.
Represent the organization in senior-level engagements, building trust with clients and internal executives through effective communication and relationship management.