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Cognizant is seeking a highly skilled and experienced Senior Data Consultant to join our team. As a Senior Data Consultant, you will play a key role in providing technology advisory services to our clients, collaborating with cross-functional teams to deliver complex projects and drive business value.
Key Responsibilities- Design and Implement Cloud-Based Data Architectures: Develop and implement cloud-based data architectures using Google Cloud, AWS, and Azure platforms, ensuring best practices and mandatory requirements are met.
- Create and Optimize Data Models and Architectures: Design and implement data models and architectures to support data analysis and business intelligence, ensuring high data quality and accessibility.
- Build and Manage Data Pipelines and Data Lakes: Develop and manage data pipelines and data lakes, ensuring high data quality and accessibility.
- Lead Data Engineering Efforts: Lead data engineering efforts, including the design and implementation of data ingestion, transformation, and consumption.
- Advise on Data Governance Strategies: Advise on data governance strategies and framework implementation to ensure data security, compliance, and quality.
- Provide Insights into Machine Learning/Artificial Intelligence Concepts: Provide insights into machine learning/artificial intelligence concepts and integrate these models into data ecosystems to drive business value.
- Oversee the Entire Data Lifecycle: Oversee the entire data lifecycle, from data creation and storage to processing and disposal, ensuring efficiency and compliance.
- Experience in Technology Services: Experience in technology services, with a strong emphasis on product design and data engineering delivery and architecture.
- Cloud Architecture Experience: Extensive experience in cloud architecture with mandatory hands-on experience in BigQuery, Snowflake, Databricks, and Synapse.
- Proven Track Record: A proven track record in guiding clients through advisory, technology selection, and solutioning, playing an outcome-focused role in leading complex transformation projects.
- Data Architecture and Modelling: Proficiency in data architecture and modelling, with the ability to create high-performance data solutions.
- Data Pipelines and Engineering: Expertise in building and delivering data pipelines and engineering, with experience in technologies like Azure Data Factory and data build tool (DBT).
- Data Governance: Experience advising and delivering on data governance within large organizations.
- Machine Learning/Artificial Intelligence: Strong understanding of ML/AI concepts and the ability to apply them within the data environment.
- Data Activation: Experience in data activation, leveraging data for operational and strategic benefits.
- Communication Skills: Excellent communication skills and the ability to discuss the enterprise-wide usage of data, with domain-specific knowledge such as Customer Data Platforms (CDP).
- Executive Relationships: Adept at building executive relationships during engagements to drive successful outcomes, uncover new consulting opportunities, and effectively position for additional consulting work with clients.
