16 days ago
Brisbane, AustraliaStaff+
Responsibilities
- Translate business requirements into scalable data, analytics, and AI platform solutions.
- Lead end-to-end delivery of enterprise data warehouse, data lake, Lakehouse, analytics, and AI initiatives.
- Design and optimize batch, streaming, API-based, and file-based ETL/ELT ingestion frameworks.
- Perform source analysis, data profiling, discovery, mapping, migration, and integration of business-critical data.
- Develop data pipelines, transformation frameworks, semantic models, and analytical solutions.
- Implement data quality, validation, governance, metadata, lineage, monitoring, reconciliation, and compliance controls.
- Design Lakehouse architectures, enterprise data models, Data Vault structures, dimensional models, and AI-ready data foundations.
- Build and integrate Azure OpenAI, RAG, vector search, AI analytics, and enterprise Copilot capabilities.
- Lead technical teams and provide guidance on architecture, modeling, AI integration, coding standards, performance, security, and cloud practices.
- Manage requirements, architecture, estimation, sprint planning, development, testing, deployment, production support, and continuous improvement.
- Drive delivery practices using Azure DevOps, Jira, and Microsoft Fabric monitoring capabilities.
- Facilitate customer engagements, AI strategy workshops, technical design sessions, solution walkthroughs, and architecture reviews.
- Define and promote enterprise data governance, security, privacy, compliance, and self-service analytics standards.
Requirements
- 16+ years of IT experience in data engineering, data warehousing, ETL/ELT development, cloud data platforms, and technical delivery leadership.
- Hands-on experience architecting enterprise-scale data engineering, analytics, and AI solutions with Microsoft Fabric, Azure Databricks, Databricks SQL, Databricks Workflows, and PySpark.
- Strong experience with distributed data pipelines, ETL/ELT frameworks, real-time and batch processing, Lakehouse and Data Mesh architectures, and cloud-native analytics platforms.
- Expertise with Microsoft Fabric components including OneLake, Lakehouse, Data Factory, Data Warehouse, Real-Time Analytics, and Power BI.
- Experience with Azure Databricks, Unity Catalog, Delta Live Tables, Delta Lake, and Azure Data Lake Storage.
- Proficiency in Python, PySpark, SQL, and Spark-based processing frameworks.
- Experience designing AI and generative AI solutions using Azure OpenAI, Azure AI Services, RAG, vector databases, AI-powered analytics, and Copilot integrations.
- Strong data modeling knowledge covering conceptual, logical, physical, dimensional, star, snowflake, Data Vault, semantic layer, and SCD Type 1 and Type 2 models.
- Experience with Azure DevOps, CI/CD pipelines, Infrastructure as Code, release management, version control, and Agile delivery.
- Knowledge of cloud architecture, performance optimization, security, governance, data quality, metadata management, master data management, and enterprise data standards.
- Experience with requirements analysis, solution architecture, estimation, resource planning, proposal preparation, technical leadership, stakeholder management, and delivery governance.
- Strong communication, presentation, consulting, leadership, and customer relationship skills.
- Microsoft Certified: DP-900 Microsoft Azure Data Fundamentals certification.
- Microsoft Certified: AZ-900 Azure Fundamentals certification.
- Databricks Data Engineer Associate Certification.
- Experience with ADF, Databricks, Synapse, Cosmos DB, and Kafka.
- Knowledge of machine learning fundamentals, prompt engineering, AI-assisted analytics, API integration, and AI model consumption.
Tech Stack
Categories
Data Engineering
About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.