AI Delivery Manager
4 weeks ago
A Day In The Life Typically Includes:
- Project Management: Oversee smaller opportunities that can be resolved quickly, focusing on data insights to solve business problems.
- Team Composition: Collaborate with EAA Leaders, Delivery managers, Project Managers, Onshore and Offshore Data Scientists, and IT/Business Subject Matter Experts.
- Leadership: Provide technical leadership, help focus on value creation and stakeholder management for multiple advanced analytics initiatives.
- Strategic Thinking: Partner with teams as an advisor, guide, and consultant to identify, implement, and champion best practices for software development.
- Technical Expertise: Proficient in AWS technologies like SageMaker, APIs, Glue PySpark/EMR, Amazon Comprehend, Textract, and other AWS services like Lambda, Glue, Batch and other data integration techniques. Demonstrate technical, team, and solution leadership through strong communication skills to recommend actionable, data-driven solutions
Strong understanding of data governance, model life cycle, AI/ML techniques, and the ability to administer technical support, security, performance tuning, and model monitoring.
- Supervisory Duties:
- Manage the delivery of data integration and application delivery projects working with product owners and delivery managers. Collaborate with team members, business stakeholders and data SMEs to elicit requirements and to develop a technical design and then implement data pipelines.
- Partner with Product teams and their leaders. Ensure all projects & Sprints are delivered on time with highest quality; positive customer feedback; Minimal escalation; Help providing estimates & highlight risks early.
- Oversee data quality checks and transmission methods and raise awareness on potential risks and issues.
- People Management and Mentoring:
- Lead offshore teams. Align team efforts with EAA and its Product teams’ goals and standards.
- Evaluate and move talent to fill roles. Continually evaluate talent strategy for short/long term needs, Strategic actions taken to keep employees motivated and focused, so they elect to remain employed and fully productive. Ensured each team member is individually optimized and turn-over is restricted to an acceptable/minimal limit.
- Guide and support team members. Actively coach using SBOs to reinforce IT vision key objective, PBM mental models, & expected performance. Be a culture carrier & promote accountability for meaningful RR&Es & development plan for each team member; Team applying PBM mental models in their day-to-day work and leading by example.
- Encourage professional growth.
- Communication:
- Excellent verbal, written and interpersonal communication skills.
- Able to manage multiple stakeholders, level set the expectations and articulate the risks and expectations to team clearly.
- Championing PBM:
- Advocate for Principle Based Management concepts.
- Implement strategies for efficiency and effectiveness.
- Emphasize integrity, stewardship, entrepreneurship, transformation, knowledge, humility, and respect as guiding principles.
What You Will Need:
Basic Qualifications:
- Bachelor’s degree in engineering (preferably Analytics, MIS or Computer Science). Master’s degrees preferred.
- Total 15-20 years of Industry experience with minimum 5 to 8 years of Data Analytics and Data Lake ETL Experience using tools like Python scripting, AWS technologies, Database.
- Data Concepts (ETL, near-/real-time streaming, data structures, metadata, and workflow management)
- Big Data experience (especially on AWS or Azure)
- Programming / Scripting (Python or Go Lang or C/C++)
- Supervisory experience – tech lead or teams focused on data or analytics.
What Will Put You Ahead?
Preferred Qualifications:
- Code Management Tools (GitLab, TFS, Azure Dev ops)
- Minimum 2 years on active Big data development experience.
- Good knowledge of cloud deployments of data engineering solutions including use of the AWS eco-system.
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