Job Description

Job Description

Must Have Technical/Functional Skills

• Strong with data modeling concepts (star schemas, snowflake schemas, highly normalized data models).

• Data modeling tools – Erwin.

• Data Warehouse database platforms – Snowflake, BigQuery, Databricks.

• Knowledge and experience of at least one data profiling tool.

• Familiar with ETL tools like DataStage/Informatica.

• Experience with AWS services including S3, Lambda, Data-pipeline, and other data technologies

• Conceptual knowledge of BI tools like Business Objects/Tableau is a plus.

• Deep understanding of principles in data warehousing and cloud architecture with principles of SQL

optimization for building very efficient and scalable data systems.

• Excellent SQL programming skills.

• Excellent problem solving skills.

• Excellent communication skills with both business and technical customers.

• Demonstrate a high level of integrity and maturity.

• Work on multiple projects and deliver consistently on time.

• Escalate issues appropriately to management and project team.

• Take a proactive approach to cross-functional communication.

• Actively seek out feedback from management and peers, to improve own performance based on that feedback

Roles & Responsibilities

• Interacting with Business Users/ Business Relationship Managers to understand the BI and analytical needs

• Identify the right data sources / data completeness to meet the BI needs.

• Data profiling to build the entity relationships across multiple sources.

• Develop and maintain data dictionary for all the data sources (existing and new ones).

• Build conceptual and logical data models considering the BI needs.

• Develop optimized database design to achieve acceptable performance by tuning views, tables for proper response time.

• Work with database administrators to implement data models into database platforms, ensuring data integrity

and consistency.

• Monitor database performance, identify bottlenecks, and optimize data models to improve query efficiency and

data access speed.

• Work closely with the IT teams in ETL design discussions adopting best practices of data load strategy.

• Identify effective reporting techniques, identify the best data sources for each report, identify risks and constraints,

and design reporting formats.

• Create and maintain metadata describing the data model, including data lineage and definitions.

• Data analyst skills to determine root cause problems for data integrity and data quality issues identified through QA

or by business report owners.

• Define data storage strategy

Generic Managerial Skills:

The BI Data Modeler will collaborate with various stakeholders from Business and other partners to understand data

requirements and business needs. Should be able to design solutions in the form of Conceptual and Logic data models

to meet business needs. Should have an ability to optimize data models for performance, scalability and ease of use.

Should have the ability to maintain accuracy, completeness and consistency of the data models with up-to-date

documentation and metadata. Shoul d be an expert in various BI tools, capture analytical and reporting requirements

from the Business, analyze various data sources and provides BI solutions that helps to facilitate reporting and

dashboarding. Should have extensive expertise on data profiling using data profile tools and modeling tools like Erwin.

Should be able to build data models by reverse engineering the database structures. Should have experience in

analyzing and handling unstructured data sources. Should have an ability to communicate complex data

concepts to non-technical stakeholders.

Design solutions based on the data lake concepts, use of data by consumers and provide solutions weighing in

pros and cons of cons ETL Vs ELT approach.

Ideal candidate is a “hands-on” type problem solver who will work directly with the data engineering and business

data management teams to help profile, catalog and design views and conceptual data model, catalog data sources

and define data quality rules based on business use cases.

Salary Range: $85,000-$120,000 a year

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