• Support the design and execution of comprehensive data migration strategies, including source-to-target mapping, transformation logic, data cleansing, and validation activities • Perform data extraction, transformation, and load (ETL) processes from legacy applications into SAP S/4HANA using SAP migration tools and related technologies • Collaborate with client stakeholders to gather migration requirements, facilitate workshops, and provide recommendations on data migration approaches and best practices • Conduct data quality assessments and participate in remediation efforts to improve the accuracy, completeness, and consistency of migrated data • Develop and maintain migration-related documentation, including mapping specifications, conversion procedures, validation results, and process workflows • Monitor migration activities throughout project execution, identify and resolve data-related issues, and support defect management processes • Assist with mock conversions, testing cycles, reconciliation efforts, and cutover planning to ensure successful migration outcomes • Provide guidance and knowledge transfer to project teams and client personnel on data migration methodologies, governance, and leading practices • Partner closely with cross-functional project teams to support implementation milestones and overall program success.

Role Description - Serve as the CEO’s right hand, acting as an extension of the CEO across priority matters. - Own CEO agenda management, including preparation for Board meetings, earnings calls, leadership off‑sites, investor interactions, and strategic reviews. - Translate CEO intent into clear priorities, actions, and outcomes across the organization. - Act as a thought partner to the CEO on strategy, organization design, leadership topics, and critical decisions. - Filter, structure, and synthesize information for decision‑making; ensure the CEO stays focused on the highest‑value issues. - Lead end‑to‑end corporate strategy formulation, including: - Medium‑ and long‑term growth strategy - Portfolio and investment strategy - Market, client, and service‑line prioritization - Inorganic growth (M&A / partnerships) support - Drive annual strategic planning, operating planning, and long‑range plans in partnership with Finance and Business Leaders. - Conduct deep‑dive analyses on growth opportunities, competitive positioning, margins, productivity, pricing, and capital allocation. - Develop Board‑level strategy narratives and materials with clarity, data, and executive polish. - Own and govern enterprise‑wide strategic initiatives, such as: - Growth acceleration programs - Margin improvement / cost transformation - Sales effectiveness and pipeline rigor - Delivery productivity and utilization - AI / digital transformation initiatives - Organization and leadership effectiveness - Set up clear charters, milestones, KPIs, and cadence for each strategic track. - Ensure cross‑functional alignment, unblock issues, and escalate decisively when needed. - Track outcomes rigorously; ensure initiatives move from ideas → execution → results. - Partner closely with CXOs and business heads to drive aligned decision‑making. - Facilitate executive forums (ELT, reviews, strategy councils) with sharp content, structure, and outcomes. - Ensure consistent messaging and alignment across leadership on priorities, trade‑offs, and commitments. - Act as a neutral integrator, balancing enterprise interests over functional silos. - Support CEO in Board engagement, including agenda shaping, materials, and follow‑ups. - Work closely with Investor Relations, Finance, and Communications on narratives, disclosures, and strategic messaging. - Occasionally engage with key customers, partners, and advisors on strategic topics. Company Description At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus. Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself. We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.

Role Description Estamos a recrutar um Data Engineer (m/f) para reforçar a nossa equipa com possibilidade de trabalhar em regime remoto. - Licenciatura em Engenharia Informática ou similares; - Mais de 3 anos de experiência em engenharia de dados ou administração de sistemas com foco em dados; - Conhecimento profundo do ecossistema Elastic (Elasticsearch, Logstash, Kibana); - Experiência com Python, Scala ou Java; - Familiaridade com gestão de grandes volumes de dados e bases de dados NoSQL; - Bons conhecimentos de SQL e modelação de dados. Qualifications - Licenciatura em Engenharia Informática ou similares; - Mais de 3 anos de experiência em engenharia de dados ou administração de sistemas com foco em dados; - Conhecimento profundo do ecossistema Elastic (Elasticsearch, Logstash, Kibana); - Experiência com Python, Scala ou Java; - Familiaridade com gestão de grandes volumes de dados e bases de dados NoSQL; - Bons conhecimentos de SQL e modelação de dados. Requirements - Licenciatura em Engenharia Informática ou similares; - Mais de 3 anos de experiência em engenharia de dados ou administração de sistemas com foco em dados; - Conhecimento profundo do ecossistema Elastic (Elasticsearch, Logstash, Kibana); - Experiência com Python, Scala ou Java; - Familiaridade com gestão de grandes volumes de dados e bases de dados NoSQL; - Bons conhecimentos de SQL e modelação de dados. Benefits - Flexibilidade no regime de trabalho (remoto); - Plano de acompanhamento regular; - Participação em projetos com tecnologia inovadora e de dimensão internacional; - Remuneração compatível com a experiência demonstrada, seguro de saúde e seguro de vida; - Dia de Aniversário e Prémio de Referências. Company Description A Movilges IT Consulting conta com mais de 30 anos de experiência no mercado Espanhol, especializada em Logística, Mobilidade e IT, oferece serviços de Consultoria, desenvolvimento de aplicações e manutenção de sistemas. Tal como o universo tecnológico, em constante evolução, também a Movilges IT Consulting pretende evoluir, aumentando a sua presença em Portugal, não só prestando os melhores serviços a parceiros e clientes, bem como oferecendo as melhores condições, benefícios e oportunidades de crescimento profissional para toda a sua equipa. - Em Portugal estamos presentes em diferentes setores, tais como, tecnologia, saúde, administração pública, energia, serviços, banca e seguros.

• Build and own ML data pipelines: Design, implement, and maintain Python pipelines that ingest, transform, and deliver datasets for model training and inference — covering use cases like [fraud detection / credit scoring / accounting automation — confirm with HM]. • Own the feature store: Design storage and access patterns for large-scale feature datasets, balancing latency and cost so ML Engineers can retrieve features reliably at both training and serving time. • Drive model serving infrastructure: Implement and maintain the infrastructure that deploys trained models into production, including versioning, scaling, and rollback. • Build data quality and drift detection systems: Work with ML Engineers to catch data issues before they degrade model performance in production — making reliability a shared standard, not an afterthought. • Set the data engineering standard: Establish reusable Python and pipeline patterns the team builds on — creating foundations, not one-off solutions.