Data Architect, Fractal
AI-driven data analytics platform
Be an early applicant
AI-driven data analytics platform
1001+ employees
Be an early applicant
1001+ employees
Company mission
To reshape business through science and advanced data tools and uncomplicate decision-making, so human intelligence can be freed from the drudgery of monotonous work and committed to the pursuit of imagination and creative rewards.
Role
Who you are
- The ideal candidate will possess a strong technical background in data architecture and engineering, with an in-depth understanding of data management principles, governance, data modeling, and cross-functional collaboration
- 7+ years of experience in data architecture, data management, or related roles, with domain expertise in specific business areas (e.g., finance, customer, product).
- Proficient in data modeling, data integration, ETL/ELT processes, and database design.
- Strong experience with data governance frameworks, metadata management, and data catalog tools.
- Familiarity with data warehousing, data lake, and cloud data platforms (e.g., AWS, Azure, Google Cloud).
- Knowledge of SQL and non-relational databases (e.g., MongoDB, Cassandra)
Desirable
- Familiarity with advanced metadata management and data catalog tools
- Experience with big data technologies and ecosystems
- Knowledge of emerging trends in data architecture and governance
- Exposure to cross-functional collaboration frameworks in large organizations
- Proficiency in performance tuning for data platforms and processes
- Understanding of advanced analytics and data science integration requirements
What the job involves
- We are seeking an experienced Data Domain Architect to lead the design, architecture, and governance of our data across specific business domains
- As a key part of our data team, you will drive the enterprise data strategy for the assigned domain(s) to ensure data consistency, quality, security, and accessibility
- Develop and maintain data architecture for assigned domains, aligning with enterprise data strategy.
- Define and implement data standards, guidelines, and best practices to enhance data quality, consistency, and reuse across systems.
- Collaborate with enterprise architects, business stakeholders, and IT teams to align data domain strategy with overall organizational objectives.
- Design conceptual, logical, and physical data models for assigned data domains, ensuring scalability, performance, and reusability.
- Lead data integration efforts to consolidate data from various sources into a unified and reliable data model.
- Partner with data engineers and developers to implement data pipelines and integration workflows.
- Enforce data governance policies and ensure compliance with regulatory standards (e.g., GDPR, CCPA, HIPAA) within the assigned data domains.
- Collaborate with data governance teams to maintain a data catalog and data lineage for transparency and accountability.
- Identify and mitigate data-related risks, including privacy, security, and data quality.
- Act as a subject matter expert for the assigned data domains, providing guidance to business and technical teams.
- Engage with business stakeholders to understand data requirements, translating them into technical specifications.
- Collaborate with data scientists, data engineers, and analysts to support data-driven insights and decision-making.
- Establish metrics and processes to monitor the performance and quality of data across assigned domains.
- Identify opportunities to optimize data architecture for scalability, performance, and cost efficiency.
- Lead data lifecycle management, including retention, archival, and deprecation of data assets.
Application process
- End Date: March 31, 2025
Salary benchmarks
Our take
The analysis of business data is essential in making operational changes based on forecasting, managing supply chains, and optimizing revenue, but the mass of available data can be overwhelming. This can sometimes be combatted with the power of AI-driven data analysis tools, but existing solutions are usually designed to solve specific problems within specialized industries.
Fractal develops AI-driven tools and platforms for businesses, including a conversational AI platform called Senseforth, a revenue growth AI tool called Samya, AI algorithms for medical imaging named Qure, and an all-in-one data analytics platform called Crux Intelligence. The company develops its solutions to be flexible and applicable within a wide range of industries including consumer packaged goods, healthcare, financial services, and media.
Whilst AI-driven business tools are commonplace, Fractal has taken the smart approach of developing a suite of flexible AI tools that can tackle problems in many industries, as opposed to focusing on a specific problem or industry. This strategy has positioned the company well for continued growth and impact, reflecting its broad applicability and potential in the market.
Steph
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 4 rounds)
Jan 2022
$360m
GROWTH EQUITY VC
Jan 2019
$200m
GROWTH EQUITY VC
Total funding: $685m
Company values
- Client first - Always do what's best for the client
- Learn and grow - Nurture and grow exceptional professionals
- Think big, act fast - Challenge the status quo and execute with speed
- Extend extreme trust and be accountable - Assume positive intent of others and hold each other accountable
Company HQ
World Trade Center, New York, NY
Articles
Leadership
Pranay Agrawal
(CEO)Experience as Associate for ANZ Grindlays Bank. Manager at ICICI bank from 1998 to 2000.
Srikanth Velamakanni
(Executive Vice Chairman)Experience as Assistant Manager of ICICI Bank. Co-founder and Trustee of Plaksha University since 2018.
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