Head of Data Platforms Practice

The Data Technology Consulting Practice is responsible for building modern and innovative technology services that 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 that 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 that deliver value?

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 support 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 skill set 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.

• 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 the 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 the 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 the 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 learned from delivery engagements to continuously improve the consulting services and Lingaro’s knowledge base.

• 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 the creation of joined consulting delivery plans.

• Lead, mentor, support, and coach data platform technology consultants and help them identify and create repeatable methodologies and templates for effectively delivering data platform solutions.

• Keep the practice at the forefront of Data Technology Consulting (by interacting with the ecosystem, attending conferences, getting certifications, interacting with external advisors, and reading articles…)

• Participate and develop personal branding in knowledge-sharing communities – internally and externally. Information Sensitivity: General\Internal

• Assess and apply the latest developments in data platform technology.

• B.Tech in Computer Science, Computer Engineering, or another engineering area.

• Must have proven experience in GCP-based data management ecosystems. One or more of the below certifications are 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 of 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 initiatives. Experience leading technology consulting practices.

• Deep practical subject matter expertise in Big Data ecosystems.

• Experienced in building relationships with directors and C-level 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 the current state, and determine maturity/readiness to execute data platform modernization.

• Expertise in industry & market trends with tools scoring model for selecting fit-for-purpose technology solutions 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 the 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 the 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 a structured approach for assessments and recommendations.

• Advise the implementation of standard operating procedures in the organization of customers' data management.

• 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 teams. Information Sensitivity: General\Internal

• 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).

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 the 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 of applications of AI to augment various data management solutions.

• Knowledge of visualization tools