Title: Architect
Area(s) of responsibility
Job Title: Senior Data Architect (Data Modeling & DB Optimization) with 11 + Yrs experience
Job Description: We are seeking a Senior Data Architect with advanced expertise in data modeling, database design, and optimization to architect high-performance, scalable data solutions. The ideal candidate will have experience designing complex data systems, optimizing databases for speed and efficiency, and ensuring that data architectures support advanced analytical and business intelligence use cases.
Key Responsibilities:
- Data Architecture Design: Lead the design and development of comprehensive data architectures, including relational, NoSQL, and cloud-based database solutions. Build logical and physical data models that can scale to handle large volumes of data and high transaction rates.
- Advanced Data Modeling: Design and implement complex data models using best practices in dimensional modeling (star, snowflake, galaxy schemas), entity-relationship diagrams (ERD), and data normalization/de-normalization for performance optimization.
- Database Performance Tuning: Apply advanced techniques such as indexing, partitioning, query optimization, caching, and materialized views to optimize database performance for both OLTP and OLAP systems.
- ETL and Data Integration: Design and implement scalable ETL pipelines to integrate data from heterogeneous sources, using tools like SQL Server Integration Services (SSIS), Apache Spark, and cloud-based data transformation services.
- Big Data Solutions: Architect and implement solutions using big data technologies (Hadoop, Spark, AWS Redshift, Azure Synapse) to handle vast amounts of unstructured or semi-structured data, ensuring data is processed efficiently and can be analyzed in real-time.
- Data Governance and Security: Ensure that data is governed in compliance with industry standards and regulations, with a focus on data quality, privacy, and security.
- Collaborate with Cross-Functional Teams: Work with data scientists, business analysts, and application developers to ensure that the data architecture is aligned with business goals, analytical needs, and application requirements.
Essential job tasks
Job Title: Senior Data Architect (Data Modeling & DB Optimization) with 11 + Yrs experience
Job Description: We are seeking a Senior Data Architect with advanced expertise in data modeling, database design, and optimization to architect high-performance, scalable data solutions. The ideal candidate will have experience designing complex data systems, optimizing databases for speed and efficiency, and ensuring that data architectures support advanced analytical and business intelligence use cases.
Key Responsibilities:
- Data Architecture Design: Lead the design and development of comprehensive data architectures, including relational, NoSQL, and cloud-based database solutions. Build logical and physical data models that can scale to handle large volumes of data and high transaction rates.
- Advanced Data Modeling: Design and implement complex data models using best practices in dimensional modeling (star, snowflake, galaxy schemas), entity-relationship diagrams (ERD), and data normalization/de-normalization for performance optimization.
- Database Performance Tuning: Apply advanced techniques such as indexing, partitioning, query optimization, caching, and materialized views to optimize database performance for both OLTP and OLAP systems.
- ETL and Data Integration: Design and implement scalable ETL pipelines to integrate data from heterogeneous sources, using tools like SQL Server Integration Services (SSIS), Apache Spark, and cloud-based data transformation services.
- Big Data Solutions: Architect and implement solutions using big data technologies (Hadoop, Spark, AWS Redshift, Azure Synapse) to handle vast amounts of unstructured or semi-structured data, ensuring data is processed efficiently and can be analyzed in real-time.
- Data Governance and Security: Ensure that data is governed in compliance with industry standards and regulations, with a focus on data quality, privacy, and security.
- Collaborate with Cross-Functional Teams: Work with data scientists, business analysts, and application developers to ensure that the data architecture is aligned with business goals, analytical needs, and application requirements.