Data Modeler - OLAP/OLTP System

Responsibilities

• Participate in requirements definition, analysis, and the design of logical and physical data models for Dimensional Data Model, NoSQL, or Graph Data Model.
• Lead data discovery discussions with Business in JAD sessions and map the business requirements to logical and physical data modeling solutions.
• Conduct data model reviews with project team members.
• Capture technical metadata through data modeling tools.
• Ensure database designs efficiently support BI and end user requirements.
• Drive continual improvement and enhancement of existing systems.
• Collaborate with ETL/Data Engineering teams to create data process pipelines for data ingestion and transformation.
• Collaborate with Data Architects for data model management, documentation, and version control.
• Maintain expertise and proficiency in the various application areas.
• Maintain current knowledge of industry trends and standards.
  

Required Skills

• Strong data analysis and data profiling skills.
• Strong conceptual, logical, and physical data modeling for VLDB Data Warehouse and Graph DB.
• Hands-on experience with modeling tools such as ERWIN or another industry-standard tool.
• Fluent in both normalized and dimensional model disciplines and techniques.
• Minimum of 3 years' experience in Oracle Database.
• Hands-on experience with Oracle SQL, PL/SQL, or Cypher.
• Exposure to Databricks Spark, Delta Technologies, Informatica ETL, or other industry-leading tools.
• Good knowledge or experience with AWS Redshift and Graph DB design and management.
• Working knowledge of AWS Cloud technologies, mainly on the services of VPC, EC2, S3, DMS, and Glue.
• Bachelor's degree in Software Engineering, Computer Science, or Information Systems (or equivalent experience).
• Excellent verbal and written communication skills, including the ability to describe complex technical concepts in relatable terms.
• Ability to manage and prioritize multiple workstreams with confidence in making decisions about prioritization.
• Data-driven mentality. Self-motivated, responsible, conscientious, and detail-oriented.
• Effective oral and written communication skills.
• Ability to learn and maintain knowledge of multiple application areas.
• Understanding of industry best practices pertaining to Quality Assurance concepts and Level :
• Bachelor's degree in Computer Science, Engineering, or relevant fields with 3+ years of experience as a Data and Solution Architect supporting Enterprise Data and Integration Applications or a similar role for large-scale enterprise solutions.
• 3+ years of experience in Big Data Infrastructure and tuning experience in Lakehouse Data Ecosystem, including Data Lake, Data Warehouses, and Graph DB.
• AWS Solutions Architect Professional Level certifications.
• Extensive experience in data analysis on critical enterprise systems like SAP, E1, Mainframe ERP, SFDC, Adobe Platform, and eCommerce systems.
  

Skill Set Required

• GCP, Data Modelling (OLTP, OLAP), indexing, DBSchema, CloudSQL, BigQuery
• Data Modeller - Hands-on data modelling for OLTP and OLAP systems.
• In-Depth knowledge of Conceptual, Logical and Physical data modelling.
• Strong understanding of Indexing, partitioning, data sharding with practical experience of having done the same.
• Strong understanding of variables impacting database performance for near-real time reporting and application interaction.
• Should have working experience on at least one data modelling tool, preferably DBSchema.
• People with functional knowledge of the mutual fund industry will be a plus.
• Good understanding of GCP databases like AlloyDB, CloudSQL and BigQuery