• Define the multi-year vision for the Data Engineering Practice, ensuring our technical capabilities are ahead of the curve for enterprise demand for Data & AI transformation. • Own the full P&L, including pipeline, pricing, delivery margin, and revenue growth, while reporting directly to executive leadership with clear commercial accountability. • Build and sustain senior relationships with Google Cloud partner teams and client executives to generate meaningful deal flow and expand strategic accounts. • Lead the practice's position on ethical AI and data democratisation while making principled, evidence-based bets on where advanced analytics and AI are creating real enterprise value. • Drive investment in reusable IP, data accelerators, and delivery assets that improve consistency, reduce time-to-value, and protect margins at scale. • Serve as a strategic advisor to client C-suite executives, helping them define data strategy, navigate AI adoption, and build the organisational capabilities to sustain it. • Set the standard for engineering and analytical excellence across the practice by hiring well, developing talent deliberately, and building teams that clients trust and return to.

• Design, develop, and maintain scalable ETL/ELT pipelines to process large volumes of data from diverse sources. • Build and optimize data storage solutions — data lakes and data warehouses — for efficient retrieval and processing. • Integrate structured and unstructured data from internal and external systems into a unified view for analysis. • Ensure data accuracy, consistency, and completeness through validation, cleansing, and transformation. • Maintain clear documentation for data processes, tools, and systems. • Build and maintain Tableau dashboards and reports that translate complex datasets into clear, decision-ready visuals. • Design data models and extracts optimized for Tableau performance, including live connections and published data sources. • Apply data visualization best practices — chart selection, layout, color, and interactivity — to produce client-ready output. • Partner with stakeholders to understand reporting needs and translate them into visual solutions. • Support ad hoc analysis using Tableau, Python-based charting (matplotlib, seaborn, plotly), or similar tools. • Support AI/ML workflows by building and maintaining the data pipelines that feed model training, inference, and evaluation. • Assist with data preparation for LLM and machine learning projects, including feature engineering, tokenization pipelines, and vector store integration. • Help teams adopt AI-assisted data tooling — copilots, intelligent search, automated reporting — by ensuring clean, well-structured data is available upstream. • Contribute to prompt engineering and evaluation frameworks where data context is a key input. • Work with product managers and stakeholders to gather requirements and translate them into technical solutions. • Provide technical input during requirements sessions to align data capabilities with business needs. • Participate in sprint planning, stand-ups, and sprint reviews. • Deliver solutions on time and within scope. Adapt when priorities shift. • Write unit and integration tests to validate pipeline reliability and data accuracy. • Identify and resolve defects, performance bottlenecks, and data quality issues. • Stay current with cloud platforms (AWS, Azure, GCP) and emerging data engineering tools. • Propose solutions to improve performance, security, and scalability.

• Collaborate with business stakeholders to understand business strategy and needs, anticipate requirements, uncovering areas for improvement and implementing solutions • Conduct thorough analysis of requests to assess feasibility, impact and alignment with strategic goals • Perform detailed requirements analysis, including definition of objectives, scope, business value and success criteria • Create clear and concise requests and project documentation, such as business cases and plans • Facilitate prioritization sessions with key stakeholders, including senior marketing team members, to evaluate and rank requests based on business value, urgency and available resources • Develop and maintain strong relationships with stakeholders to understand needs, gather feedback and ensure alignment between business objectives and analytics initiatives • Communicate project priorities and timelines effectively to cross-functional teams • Work closely within the EDO to define deliverables, create data requirements and define or recommend analytical methodologies • Provide guidance and support to EDO pods throughout development cycle • Review and validate analytical outputs, ensuring accuracy, consistency and alignment with business requirements • Serve as a liaison between EDO team and business stakeholders • Monitor project progress and timelines using Azure DevOps and PowerBI, proactively identifying and addressing potential roadblocks or delays • Prepare regular project status reports and communicate updates to stakeholders • Conduct post-delivery evaluations to assess performance, identifying areas for improvement and capturing lessons learned for future initiatives

Role Description The Data Entry Associate is responsible for accurately entering, updating, and maintaining information across digital systems, spreadsheets, and databases. This role is ideal for someone who is detail‑oriented, organized, and comfortable working independently in a remote environment. The position requires a high level of accuracy, consistency, and the ability to manage repetitive tasks while maintaining quality standards. In this role, the associate will support various departments by processing data, reviewing records for completeness, and ensuring information is properly formatted and stored. The ideal candidate thrives in a structured workflow, communicates clearly, and can manage deadlines without direct supervision. Training is provided, and high performers may have opportunities to grow into data quality, reporting, or operations support roles. Key Responsibilities - Enter, update, and maintain data in spreadsheets, databases, and internal systems - Review information for accuracy, completeness, and consistency - Clean, organize, and standardize data across multiple sources - Identify errors or discrepancies and correct or escalate as needed - Maintain confidentiality and follow data‑handling guidelines - Assist with generating basic reports or summaries when requested - Manage daily data entry tasks and meet productivity expectations - Support team members with administrative or data‑related tasks Qualifications - Strong attention to detail and accuracy - Fast and consistent typing skills (40+ WPM preferred) - Comfort working with spreadsheets (Excel or Google Sheets) - Ability to follow structured workflows and instructions - Strong organizational and time‑management skills - Ability to work independently in a remote environment - Reliable internet connection and computer access Requirements - Previous experience in data entry, administrative support, or similar roles - Familiarity with CRM systems or data management tools - Basic understanding of data cleaning or formatting - Experience working in remote or distributed teams Benefits - This is a fully remote position with flexible scheduling depending on business needs - The work environment is structured, supportive, and focused on accuracy and efficiency - Compensation includes a competitive hourly rate - Paid training - Opportunities for advancement into data quality, reporting, or operations roles