Data Architect, Data Scientist Sr,Data Scientist Jr.

Company Description

namsbel provides strategic and systematic solutions to business problems across various verticals using a global network.

Role Description: The data architect is responsible for designing, creating, and managing an organization’s data architecture. This role is critical in establishing a solid foundation for data management within an organization, ensuring that data is organized, structured, accessible, secure, and aligned with business objectives.

Responsibilities

● Interact & Influence business stakeholders to secure strong engagement and ensures that the data & analytical product delivery aligns with longer-term strategic roadmaps

● Design & contribute towards the structure and layout of lake house architecture optimizing data storage, and establishing data access controls and security measures

● Implement the long-term Data & Analytics strategy and deliver functional objectives

● Assess requirement feasibility, translates high-level business requirements into data requirements, appropriate metadata, test data, and data quality standards

● Explore Data Sources by working with Application owners to confirm datasets to be extracted

● Contribute to establishing and implementing database structure, including schema design, table definitions, column specifications, and naming conventions

● Design Data models for Source data products, Master data products & Insight data products.

● Document Data Architecture artifacts for different Data Products and solutions and perform peer review across various functions.

● Support Data Engineering and BI Engineering teams during the build phase

● Review Data models development, validate and provide deployment approval

● Work closely with data stewards and governance functions to continuously improve data quality and enhance the reliability of data model(s).

● Simplify the existing data architecture, delivering reusable services and cost-saving opportunities in line with the policies and standards of the company

● Leads and participates in the peer review and quality assurance of project architectural artifacts across the Data Architecture group through governance forums

● Collaborate and contribute to the development and enhancement of standards, guidelines, and best practices within Data Architecture discipline.

● Works with Product owners, Business stewards, Data Scientists and end users to understand data consumers’ needs and develop data products/ data solutions

● Evaluates and recommends emerging technologies for data management, storage, and analytics

Education

● A bachelor’s degree in computer science, data science, engineering, or related field

Experience

● At least five years of relevant experience in design and implementation of data models for enterprise data warehouse initiatives

● Translate business requirements and ability to guide solution design & architecture in developing Data Products

● Develop scalable, high-performance, and reusable data models that can be efficiently utilized across different data initiatives and help in generating actionable insights

● Work collaboratively with data stewardship and governance functions to continuously improve data quality and enhance the reliability of data models

● Ability to navigate and collaborate with cross-functional teams involving data scientists, business analysts, and stakeholders

● Strong Business Process and Functional understanding with an Analytical background

● CPG experience with knowledge in domain specific concepts is a plus

● Knowledge on Agile methodologies with experience working on tools such as Jira & Confluence

Skills

● Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake)

● Experience with database technologies such as SQL, NoSQL, Snowflake, HANA

● Understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques

● Experience building enterprise data models (Logical, Physical, Conceptual) and data modeling tool experience a plus (ERWIN, ER/STUDIO, etc.)

● Strong Business Process and SAP functional understanding with an analytics background (preferred SAP ECC/S4, BW, HANA, BI, ARIBA experience) is a plus

● Expert-level SQL skills

● Experience with enterprise scale data engineering orchestration frameworks/ELT tools and common data engineering Python libraries (dbt, pandas, great expectations, etc.) is a plus

● Experience with business intelligence tools and technologies such as Power BI & Tableau

● Strong analytical and problem-solving skills

● Understanding of Data Governance principles and practices including Data Quality, Data Security and compliance

● Ability to think strategically on the use of data within the Organization that support both current and future needs.

• ● Excellent communication and interpersonal skills for stakeholder management and cross-functional collaboration.