We’re a global technology and services leader that powers the brands of the future. We help well-known brands — the ones you use every day — improve their businesses with technology and integrated solutions, in over 70 countries.
Maintain our overall data architecture strategy, including data models, data integration, data governance, and data quality standards.
Design and implement scalable and efficient databases, data warehouses, and data lakes to support our needs and analytics projects. Experience with dimensional data modeling, RDBMS and NoSQL platforms.
Manage the full life cycle of data warehouse and big data solutions. This includes creating the requirements analysis, the platform selection, design of the technical architecture, design of the application design, testing, and deployment of the proposed solution.
Collaborate with partners, such as business analysts, data scientists, and IT teams, to understand data requirements and translate them into data solutions.
Benchmark systems, analyze system bottlenecks and propose solutions to eliminate them.
Evaluate and select appropriate technologies to support our data architecture strategy.
Guide/Mentor/Help develop the proposed architectural solution.
Lead performance tuning and optimization activities of the data systems
Lead the team in infrastructure setup phases.
Take end-to-end ownership for solution components and bring in design best practices and tools. Define data integration and ETL (Extract, Transform, Load) processes to ensure smooth data flow between systems and data sources.
Establish and enforce data governance practices, including data security, data privacy, and data access controls.
Skills:
8 years work experience as a data architect (enterprise level)
Minimum 5+ years' experience in Data Warehouse design for complex Data Platform. Experience with star schemas, dimensional modeling, and extract transform load (ETL) design.
Knowledge of data modeling using Kimbal and Inmon methodologies
Recent 5+ years in Big Data Ecosystem. Expertise in cloud-based data platforms, such as AWS OR GCP. In-depth knowledge of data modeling concepts and techniques, including relational, dimensional, and NoSQL data models.
Python expert responsible for designing, coding development projects related to data pipelines that create data for valuable insights.
Expert understanding of architectural and data warehouse design principles and data integration.
Expert with data integration technologies like Kafka and Spark.
Knowledgeable of any of the ETL technologies like Pentaho, SSIS, Informatica or DataStage.
Experience working with RDBMS like Oracle, SQL Server, MySQL and Postgres.
Knowledge of data governance practices, data security, and privacy regulations (e.g., GDPR, CCPA).