Lead complex, multi-person, or high-value data AI engagements (Data Warehouse, Data Lakehouse projects)
Strong technical understanding of Databricks/Azure/SQL/PySpark to facilitate technical discussions and handle escalations
Proven experience managing data engineering, cloud data warehouse projects (Azure, AWS, Databricks, Snowflake)
Requirements:
Leads the delivery of data initiatives (data engineering, BI, analytics), ensuring timely implementation and adhering to scope and budgets
Acts as the primary point of contact between project sponsors, business stakeholders, and technical teams to align goals and manage expectations
Forecasts demand, manages resource capacity, and assigns data personnel to projects efficiently
Identifies, mitigates, and resolves data-related risks and blockers throughout the project lifecycle
Job description
This is a remote position.
Project Delivery & Execution: Leads the delivery of data initiatives (data engineering, BI, analytics), ensuring timely implementation and adhering to scope and budgets.
Stakeholder Management: Acts as the primary point of contact between project sponsors, business stakeholders, and technical teams to align goals and manage expectations.
Resource Planning & Allocation: Forecasts demand, manages resource capacity, and assigns data personnel to projects efficiently.
Risk & Issue Management: Identifies, mitigates, and resolves data-related risks and blockers throughout the project lifecycle.
Process & Quality Improvement: Implements best practices in data governance, ensures data quality, and drives continuous improvement using tools like JIRA or Azure DevOps.
Team Leadership: Mentors and manages technical team members, fostering collaboration and ensuring high performance.
Backlog & Requirement Prioritization: Supports the definition of user stories and prioritizes the project backlog.
Strong experience in data & analytics (e.g., Python, SQL, cloud data platforms).
Proficiency in project management methodologies (Agile, Scrum, Waterfall).
Excellent communication, negotiation, and stakeholder management skills.
Requirements
Job Description
12 – 15 years of experience in Data & Analytics area
Lead complex, multi-person, or high-value data & AI engagements (Data Warehouse, Data Lakehouse projects)
Strong technical understanding of Databricks/Azure / SQL / Pyspark to facilitate technical discussions and handle escalations.
Proven experience managing data engineering, cloud data warehouse (Azure, AWS, Databricks, Snowflake) projects
Experienced in Agile (Scrum/Kanban) methodologies to manage project backlogs, sprints, and deliverable quality.
Proactively identify project risks, develop mitigation plans, and manage scope changes to prevent overruns
Strong leadership, communication, and client-facing skills in high-paced environments.
Act as trusted advisors to customers, manage cross-functional teams and align technical milestones with business goals
Benefits
Diversity Inclusion:
At Exavalu, we are committed to building a diverse and inclusive workforce. We welcome applications for employment from all qualified candidates, regardless of race, color, gender, national or ethnic origin, age, disability, religion, sexual orientation, gender identity or any other status protected by applicable law. We nurture a culture that embraces all individuals and promotes diverse perspectives, where you can make an impact and grow your career. Exavalu also promotes flexibility depending on the needs of employees, customers and the business. It might be part-time work, working outside normal 9-5 business hours or working remotely.. We also have a welcome back program to help people get back to mainstream after a long break due to health or family reasons.
