Project Manager - Enterprise Datalakes Project

About the Opportunity

We are seeking an exceptional, delivery-focused Contract Project Manager to lead our strategic Enterprise Data Lake Implementation. In this high-visibility role, you will be responsible for orchestrating the end-to-end delivery of a next-generation centralized data architecture designed to unify disparate operational systems, scale analytical capabilities, and support enterprise-grade business intelligence and machine learning initiatives.

The ideal candidate possesses a deep blend of technical data fluency and robust project governance skills. You will sit at the intersection of business strategy, data engineering, enterprise architecture, and information governance, ensuring that complex data migration, storage, and processing pipelines are delivered on time, within scope, and aligned with industry-leading standards.

Role Summary

As the Project Manager for our Enterprise Data Lake initiative, you will drive project planning, resource allocation, risk mitigation, and executive communications. You will oversee multi-disciplinary technical teams—including Data Architects, Data Engineers, BI Developers, and Security Specialists—working on modern cloud-based data ecosystems (AWS, Azure, or GCP-based platforms using tools such as Snowflake, Databricks, Spark, and Delta Lake).

We require a professional with 5 to 15 years of progressive experience who can quickly grasp complex technical environments, translate business needs into actionable data milestones, manage multi-vendor environments, and enforce rigorous delivery practices.

Detailed Roles & Responsibilities

Your responsibilities will span the entire project lifecycle, requiring a hands-on approach to both strategic roadmap alignment and daily execution management.

1. Project Leadership & End-to-End Governance

• Define, baseline, and manage the comprehensive project management plan, including work breakdown structures (WBS), resource plans, delivery schedules, and budget allocations for the data lake initiative.
• Establish, tailor, and maintain agile, waterfall, or hybrid delivery frameworks (Scrum/Kanban) best suited for complex data engineering and infrastructure tracks.
• Manage technical dependencies across internal lines of business, legacy database source systems, infrastructure teams, and downstream analytics consumers.
• Conduct rigorous stage-gate reviews and ensure formal sign-offs across architectural design, Proof of Concept (PoC), Minimum Viable Product (MVP), and production rollout phases.

2. Data Lake Delivery & Technical Coordination

• Coordinate the deployment of scalable enterprise data lake repositories, overseeing data ingestion (batch and real-time streaming), storage optimization, cataloging, and compute layers.
• Collaborate closely with Lead Data Architects and Engineers to monitor sprints addressing schema designs, data modeling, ETL/ELT pipeline construction, and API data services.
• Facilitate the technical integration between raw storage zones (Bronze/Landing), cleansed and standardized layers (Silver), and curated business-ready semantic models (Gold).
• Ensure data pipeline performance, scalability testing, and disaster recovery validation meet documented Service Level Agreements (SLAs).

3. Stakeholder Management & Communications

• Serve as the primary liaison between technical teams, business analytics groups, compliance officers, and executive steering committees.
• Translate complex technical concepts, such as distributed computing, metadata tagging, and pipeline orchestration, into business-oriented status reports and value realization metrics.
• Lead weekly status meetings, sprint planning, sprint retrospectives, backlog grooming, and executive bi-weekly Steering Committee presentations.
• Manage external third-party software vendors and systems integration consulting partners, ensuring contract deliverables and statements of work (SOWs) are met.

4. Risk, Issue, and Scope Management

• Proactively identify, quantify, and mitigate technical and operational risks related to data loss, schema drift, network throughput, security vulnerabilities, and vendor performance.
• Enforce formal change control procedures to manage scope creep while remaining agile enough to accommodate critical, evolving analytical priorities.
• Quickly resolve cross-functional bottlenecks, unblock engineering teams, and negotiate conflict resolution across competing domain data requests.

5. Data Governance, Quality, and Compliance Assurance

• Ensure strict adherence to enterprise data governance policies, including role-based access control (RBAC), data encryption (at rest and in transit), and data masking techniques.
• Partner with compliance teams to satisfy regulatory constraints, such as GDPR, CCPA, HIPAA, or SOX, within the data lake boundary.
• Oversee the definition and enforcement of automated data quality frameworks to monitor data completeness, consistency, timeliness, and validity across all ingested sources.

Required Skills and Qualifications

Candidates must meet the following criteria to be considered for this engagement:

• Work Experience: 5 to 15 years of dedicated project/program management experience, with a heavy emphasis on enterprise-scale data, business intelligence, and cloud transformation programs.
• Subject Matter Expertise: Strong working knowledge of Modern Data Stack concepts: Enterprise Data Lakes, Data Warehouses, Data Lakehouses, Delta Lake architecture, distributed storage, and big data ecosystems.
• Cloud Ecosystems: Proven experience delivering data solutions hosted on major cloud service providers (Amazon Web Services, Microsoft Azure, or Google Cloud Platform).
• Data Platform Familiarity: Solid understanding of tools such as Snowflake, Databricks, Apache Spark, Kafka, AWS S3, Azure ADLS/Synapse, Airflow, and dbt. While coding is not required, technical literacy to challenge timelines and architecture is mandatory.
• Project Management Competencies: Mastery of project management methodologies (Agile, Scrum, Waterfall, Hybrid). Proficiency with modern PM tools like Jira, Confluence, Microsoft Project, and Smartsheet.
• Soft Skills: Exceptional verbal and written communication skills, conflict resolution abilities, executive presentation skills, and the capacity to lead matrixed teams without direct reporting authority.
• Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, Business Administration, Engineering, or a related field.

Preferred Certifications

• Project Management Professional (PMP) or PRINCE2 Practitioner.
• Certified ScrumMaster (CSM), PMI-Agile Certified Practitioner (PMI-ACP), or SAFe Agilist.
• Cloud or Data Architecture Fundamentals (e.g., AWS Certified Cloud Practitioner, Azure Fundamentals, Databricks Certified Associate, Snowflake Core).

Key 12-Month Deliverables

During the contract tenure, the Project Manager will be evaluated on the successful completion of the following milestones:

1. Establishment and baseline of the master Enterprise Data Lake Project Charter, integrated project plan, and governance cadence within the first 30 days.
2. Successful delivery of the foundational Cloud Data Lake Infrastructure and security boundary setup (Landing, Cleansed, Curated layers).
3. Migration and pipeline implementation for initial top-priority source systems into production within the agreed-upon timeline.
4. Implementation of automated data validation and data cataloging processes across all ingested feeds.
5. Transition documentation, operational runbooks, and handover sessions to the permanent Data Operations and Support teams.