T&T | EAID | Engineering | Google Data Architect | Hyderabad

The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.

Your work profile

• Strong experience in Asset Management / Private Markets data models, including Fund, Vehicle, Investor, Asset, Position, Transaction, NAV, GL, Cashflow, Fee and Performance datasets.
• Good understanding of ABOR and PBOR concepts, including fund accounting, capital activity, valuation, investor reporting, IRR, TVPI, DPI, RVPI, track record and fee calculations.
• Experience working with Fund data and translating source structures, business rules, and reporting requirements into scalable Data Mart models.
• Ability to work with business SMEs, Data Managers and delivery teams to define entity relationships, table grain, hierarchies, and reusable mart patterns.

Key Required skills

• Hands-on experience in conceptual, logical, and physical data modelling for enterprise data warehouses and cloud data platforms.
• Strong knowledge of facts, dimensions, conformed dimensions, bridge tables, hierarchies, SCD Type 1 / Type 2 and dimensional modelling patterns.
• Experience creating source-to-target mappings, data dictionaries, attribute definitions, lineage, metadata, and modelling standards.
• Good understanding of SQL, ETL/ELT, dbt transformation patterns, data quality, reconciliation, and analytics consumption layers.
• Exposure to Airflow-based orchestration and understanding of how data models are operationalised through scheduled pipelines, dependencies, and batch processing.
• Experience with platforms such as GCP BigQuery, Snowflake, Databricks, Azure Synapse or similar is preferred.
• Ability to support complexity assessment, model reviews, engineering handover and documentation for downstream data engineering and reporting teams.

Qualifications

• Education - B. tech or BE

Location - Hyderabad