Data Technology Consultant

Responsibilities

• Support and contribute to Data Analytics strategy and consulting engagements, helping clients identify and maximize the value of their data initiatives
• Evaluate and recommend data technology options, assessing their fit with clients' strategic vision and business objectives
• Support digital transformation activities, including documenting current data architectures and identifying opportunities for improvement
• Maintain up-to-date knowledge of technical solutions, architecture trends and best practices, contributing as a Data Solution Architect where needed
• Build strong client relationships, communicate clearly with stakeholders and advocate for technology options by presenting models to support client decision-making
• Collaborate with internal, client and third-party teams to drive successful delivery through an integrated model
• Support the implementation of data governance frameworks, data quality practices and data privacy compliance across client engagements
• Contribute to AI/ML-enabled data solutions and assist in advising clients on Generative AI adoption, covering data readiness, responsible AI and governance alignment
• Contribute to business development activities, including case studies, content creation and identifying new client opportunities

Languages

Required

• Proficiency in at least one of the following: Data Engineering, cloud data warehousing (e.g. Snowflake, BigQuery, Redshift, Azure Synapse), BI and visualization tools (e.g. Power BI, Tableau, QlikView, Looker), distributed data processing (e.g. Spark, Kafka, Databricks, MS Fabric) or Data Science and ML
• Good working knowledge of at least one major cloud provider (AWS, Azure or GCP)
• Working knowledge of data governance frameworks and data privacy regulations across major jurisdictions
• Proven experience delivering projects within Agile or Scrum frameworks, with a solid understanding of SDLC principles and CI/CD practices in data environments
• Working knowledge of business analysis techniques, including requirements gathering, user story definition and project documentation

Nice to have

• Strong communication and stakeholder management skills – able to translate technical concepts for business audiences and confidently present and advocate technology recommendations to clients
• Hands-on experience with AI/ML frameworks or cloud AI platforms
• Familiarity with Generative AI tools, LLM integration patterns or prompt engineering
• Practical experience with MLOps tooling

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