Data Architect, Analytics Products, Route to Market - Bengaluru, Karnataka, India - Unilever

Unilever

Verified Company

Bengaluru, Karnataka, India

1 week ago

Posted by:

Deepika Kaur

beBee Recuiter

Description

JOB TITLE:
Data Architect, Analytics products, Route to Market***
LOCATION:UniOps
BANGALORE

MAIN JOB PURPOSE:

HUL has been a pioneer in the FMCG space for many decades now. One of the key differentiating factors which keeps it ahead of the curve is its investment in technology.

With this role, the individual stands a chance to be in the driver's seat to use technology to drive sales, while building a robust understanding of the consumer goods space.

The technology we design, build, and deploy here, gives HUL the cutting edge to go to market with best-in-class products.

This position plays a pivotal role in design and, delivery of critical data platform in CD, in close partnership with external partners, product owners and centre of excellence teams.

This is the best role at the intersection of business, data and technology.

JOB SUMMARY

Qualifications:

Data Warehousing - Bigqeury, Snowflake; Data base management - MySQL, SQL Server, NoSQL databases, Cassandra; Query languages - PL/SQL, T-SQL; Knowledge on Cloud Database Services like Google Cloud SQL, Microsoft Azure SQL Databas, NewSQL Databases - NuoDB, Cloud Spanner.

Knowledge on Containerization and Orchestration

Key Responsibilities:

Data Modelling and Design:

Develop and maintain conceptual, logical, and physical data models that represent the organization's data landscape.
Expertise in database design principles, normalization, and denormalization. Knowledge of data modelling tools and techniques. Design and implement database structures, ensuring scalability, performance, and security.

Database Management & Integration

Oversee the installation, configuration, and maintenance of database management systems.
Define and implement data governance policies and procedures to ensure data integrity, security, and compliance.
Collaborate with data engineers to design and implement efficient data integration processes.
Identify opportunities for performance improvement in data retrieval and analysis. Implement best practices for indexing, partitioning, query optimization and finetune database configurations for optimal performance.

Data Quality and Security:

Implement strategies to enhance data quality, accuracy, and consistency.
Establish and enforce data security measures to protect sensitive information.
Data Replication and High Availability
Knowledge of data replication strategies, high availability configurations, and disaster recovery planning.

Metadata Management:

Develop and maintain metadata repositories to document data definitions, lineage, and relationships.
Facilitate the use of metadata for data discovery, analysis, and reporting.

Integration with different streams, global teams and external partners. Engagement with product partners & service providers to bring outside-in view.

Governance & Collaboration

Collaboration and Communication: Effective communication skills to collaborate with crossfunctional teams, developers, and other stakeholders.
Understanding of version control systems, such as Git, for managing database schema changes and versioning
Collaboration with data engineering, analytics, and business teams