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 procedures.

Education/Experience 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