HEAD OF DATA PRACTICE - GOOGLE CLOUD PLATFORM SENIOR - REMOTO

Hiring- Data Head Practice (Data and Analytics) Remote in Mexico  About our Team  The Data Technology Consulting Practice is responsible for building modern and innovative
technology services which enable our customers to successfully realize value from data. Currently,
the Practice focuses on four data technology domains:  • Data strategy: How to deliver a structured approach to design and execute data
and analytics programs which are linked to an organization’s business strategy? • Data platforms: How to optimize existing data platform architectures and
technology designs to improve technical and cost performance?  • Data management: How to govern and manage data more efficiently, enabling
organizations to achieve better business outcomes?  • Data visualization: How to enable visual data communication in organizations and
realize value from data through actionable insights which deliver value?
Who we are looking for
We are looking for a seasoned leader with a strong consulting, data technology, and data
management background, who will shape Lingaro’s Data Platform Practice.
The position will drive the aforesaid practice with a mission to supporting our customers to maximize
the ROI of all data related investments through optimization of existing or migration to modernized
data platforms promising a robust architecture, better data management and improved
performance. This is a high growth area and a high visibility role with plenty of opportunities to
enhance your skillset and build your career working for Fortune Global 500 companies. The role will
report to the Head of Data Technology Consulting and will be part of the Data Technology Consulting
leadership team.
We are looking for an experienced leader with a hands-on technical background and a proven track
record in the same or similar Head level role in a well-established consulting company.  Responsibilities  • Creating a long-term strategy to develop the Data Platform Practice with the
respective team, capabilities and client offering portfolio to meet current and new
unmet demand from customers and market.  • Support in the generation of leads through thought leadership: articles, analysis,
white papers, public presentations, webinars etc.  • Gather outside-in perspective, generation/adoption/implementation of innovative
ideas, and development of accelerators.  • Advising and working with senior client executives on how to govern, process and
manage data more effectively, and implement modern and innovative technology
solutions, becoming the “trusted advisor”.  • Lead technology assessments to help clients improve capabilities from current state
to the target state of maturity by creating technology roadmaps and implementation
plans together with quantified value realization measures.  • Lead the effective collaboration with sales and account management to cater to
needs of both new and existing customers.  • Provide technical pre-sales services to customers and participate in the creation of
customer proposals, statement of work (SOWs) and project scoping calls.  • Collection of lessons learnt from delivery engagements to continuously improve the
consulting services and Lingaro’s knowledgebase.  • Support knowledge and skills capacity enablement in Delivery teams.  • Collaborate with Lingaro’s technology Partners to evolve existing frameworks,
methodologies, and best practices in the delivery of data technology engagements and
creation of joined consulting delivery plans.  • Lead, mentor, support and coach data platform technology consultants and help
them in identifying and creating repeatable methodologies and templates for effectively
delivering data platform solutions.  • Keep the practice at the forefront of the Data Technology Consulting (by interacting
with the ecosystem, attending conferences, getting certifications, interactions with
external advisors, reading articles…)  • Participate and develop personal branding in knowledge sharing communities –
internally and externally • Assess and apply the latest developments in data platforms technology.  Required Skills, Knowledge and Experience   B.Tech in Computer Science, Computer Engineering, or another engineering area.  • Must have proven experience on GCP based data management ecosystems. One
or more the below certifications needed:
• GCP Certified Professional Cloud Architect.
• GCP Certified Associate Cloud Engineer.
• GCP Certified Professional Data Engineer.  • Experience in building data management solutions on at least another cloud
platform such as Azure and AWS
• 15+ years hands-on experience in multiple data management areas such as data
architecture, data platform solution architecture, data modeling, data quality and
observability, data stewardship, master data management, metadata
management, data operations, data security etc.  • Excellent command over implementation of modern data architectures such as
Data Fabric, Data Mesh, and Data Lakehouse.
• Experience in implementation of solutions leveraging commercial or open-source
products in data cataloging, data quality, and/or observability.  • 7+ years in a consulting role leading Data Platform development
initiative. Experience leading technology consulting practices.  • Deep practical subject matter expertise in Big Data ecosystems.  • Experienced in building relationships with directors and C-levels stakeholders by
developing a deep understanding of the customer business and driving data-driven
insights.  • Hands-on experience in running customer workshops and other collaboration
sessions to discover customer priorities, understand current state, and determine
maturity/readiness to execute data platform modernizations.  • Expertise on industry & market trends with tools scoring model for selecting fit for
purpose technology solution and tailoring and applying industry best practices at scale. • Deep understanding of modern technology trends and data stacks in data
management and governance.  • Experience in definition and development of new consulting service offerings as well
as developing white papers and best practices.  • Ability to deliver consulting services to:  • Help our customers better leverage native services on cloud to deliver a
highly efficient data management and governance ecosystem.
• Recognize functionality gaps in cloud native services with respect to
customer’s requirements and propose alternate yet synergistic solutions for
better data management and governance.
• Delivering structured approach for assessments and recommendations.
• Advise implementation of standard operating procedures in customer’s data
management organization.
• Support data platform modernization with modern architectures, and
technologies including GenAI.
• Support in the development of migration and adoption strategies that
accelerate customer business value realization.
• Contribute to the creation of cloud-based architecture blueprints and best
practices.
• Willingness to travel on business (0-30%).  • Consulting mindset, true interest, and motivation to engage in assessment and
optimization projects.  • Ability to coach, manage and develop diverse technology team • Excellent English written and verbal communication skills for technical writing and
business presentations.  • Familiarity with Cloud Architecture Frameworks (Cloud Adoption Framework, Data
Cloud, Well Architected frameworks).   Good to Have Skills:  One or more of the below mentioned certifications will be a big plus:
• Certifications in data management tools such as: Alation, Atlan, Collibra, Unity Catalog,
TIBCO, Talend, Reltio, Precisely, Ataccama, Great Expectations etc.
• Microsoft Azure Solutions Architect Expert. Microsoft Fabric Analytics Engineer Associate.
• Databricks certified Data Engineer Professional.
Knowledge in following areas will be good to have:
• Exposure to various data governance operating models and associated standard
operating processes, metrics, roles, and responsibilities.
• Experience in the implementation master and reference data management for
analytical or operational purposes.
• Experience in implementing microservices architecture and real-time data integration.
• Knowledge of industry-specific data quality or data security practices and regulations.
• Knowledge in applications of AI to augment various data management solutions.
• Knowledge in visualization tools