Architect of Analytics Engineering, Algolia

Salary not provided
Python
Tableau
Looker
Redshift
Git
dbt
Mid and Senior level
London
Algolia

Site search and discovery powered by AI

Be an early applicant

Algolia

Site search and discovery powered by AI

501-1000 employees

B2BArtificial IntelligenceEnterpriseAnalyticsBusiness IntelligenceAPIeCommerce

Be an early applicant

Salary not provided
Python
Tableau
Looker
Redshift
Git
dbt
Mid and Senior level
London

501-1000 employees

B2BArtificial IntelligenceEnterpriseAnalyticsBusiness IntelligenceAPIeCommerce

Company mission

Algolia's mission is to change the way people interact with data.

Role

Who you are

  • This is a role that requires someone with excellent knowledge and experience of developing scalable, performant and well-governed analytical data architectures
  • Knowledge of the various data architectures that can be implemented (Warehouse, Lakehouse, Data Mesh, Data Fabric, Data Vault etc.)
  • Knowledge of the various types of physical data modeling approaches including kimball
  • Have led the strategy and implementation of a data architecture in a previous role
  • Bachelor's or Master’s degree in technical discipline; Master's preferred
  • Familiarity with Git
  • Ability to thrive in a fully remote organization
  • Positive and solution-oriented mindset
  • Comfort working in a highly agile, intensely iterative environment
  • Self-motivated and self-managing, with task organizational skills
  • Great communication: Regularly achieve consensus amongst technical and business teams
  • Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations
  • 3+ years managing the same data model system over time, evolving the model to meet new business requirements
  • Experience working with commercial data warehouses, ETL tools, data visualization and Data Dictionary tools (Redshift, Meltano, Dbt & Python scripts, Thoughtspot, Looker, Tableau, HEX, Atlan)
  • Demonstrated experience leading 2 or more multi-department analytics projects from inception to operationalization
  • Demonstrated proficiency with data system design, including databases, schema, marts, aggregates, and views
  • Experience with data access and security techniques, both inside and outside of a data warehouse
  • Experience with data pipelines in support of near real-time event stream processing
  • Created and presented multi-quarter development roadmaps to non-technical audiences
  • WE’RE LOOKING FOR SOMEONE WHO CAN LIVE OUR VALUES:
  • GRIT - Problem-solving and perseverance capability in an ever-changing and growing environment
  • TRUST - Willingness to trust our co-workers and to take ownership
  • CANDOR - Ability to receive and give constructive feedback
  • CARE - Genuine care about other team members, our clients and the decisions we make in the company
  • HUMILITY - Aptitude for learning from others, putting ego aside

What the job involves

  • Algolia is looking for an Analytics Architect, who will work at the intersection of Business Teams, Data Analytics and Data Engineering
  • They will possess an excellent understanding of developing and governing conceptual, logical and physical data models
  • They will be responsible for putting the structure and processes in place to ensure the analytical data architecture meets the current business needs and future needs
  • The Data Warehouse is positioned as the single source of truth for Algolia’s corporate data, performance analytics, and company-wide data such as Key Performance Indicators
  • The Data Platform supports Algolia’s data-driven initiatives by providing all teams a common platform and framework for reporting, dashboarding, and analytics
  • With the exception of point-to-point application integrations all current and future data projects will be driven from the Data Platform
  • As a recipient of data from a variety of Algolia’s source systems, the Data Platform will also help inform and drive Data Quality best-practices, measures, and remediation to help ensure all decisions are made using the best data possible
  • Define the analytical data architecture principles, standards and guidelines and put controls in place to ensure these are followed
  • Have an in-depth knowledge of physical data modeling approaches including but not limited to kimball
  • Have experience of developing and managing conceptual, logical and physical data models
  • Critically assess the performance, scalability, access, governance etc. of the data architecture and put key indicators in place to monitor
  • Continuously review current data modeling principles and initiate any improvements to enable the implementation of the intended architecture
  • Create a shared understanding between the business teams and the data teams
  • Review and improve the data system as a whole, inclusive of data model designs, process flows, and end use cases
  • Have a strong understanding of building a compliant and secure data warehouse
  • Have a strong understanding of data access and control strategies
  • Applying knowledge of best data architecture practice and architecture documentation to manage current state of architecture and manage implementation of future state
  • Collaborate with people in the business to collect business requirements, design the conceptual and logical data models
  • Create automated governance processes that assures adoption, monitors and enforces the adoption of best practices in data architecture
  • Monitor the usage of the data warehouse and identify areas for improvement
  • Update key stakeholders on any changes to the data architecture
  • Approve key data model changes as a Reviewer and code owner for database and data model schemas
  • Contribute towards the Data Catalog, a scalable resource to support Self-Service and Single-source-of-truth analytics
  • Lead governance projects related to the architecture
  • Ensuring the most appropriate security and compliance practices are embedded in the data architectural strategy

Salary benchmarks

Our take

While in-site searching has been available for some time from web search servers such as Google and Bing, its functionality is limited due to it relying on general web scraping techniques which can miss relevant information. By contrast Algolia indexes only the company's site, allowing its search to serve accurate results extremely swiftly, which helps to drive sales conversions aside from making sites far more usable. The efficacy of this solution can be seen from its customer base of over 10,000 companies including the likes of Slack, Zendesk and Lacoste.

To diversify and increase the product range, Algolia have expanded into other real-time APIs such as product recommendations available for eCommerce websites. With the company performing extremely well over the last few years, Algolia have recruited key senior executives to futher its growth. As the company continues to scale it seems likely that an IPO is not too distant a prospect.

Freddie headshot

Freddie

Company Specialist

Insights

Led by a woman
Top investors

Few candidates hear
back within 2 weeks

33% female employees

-3% employee growth in 12 months

Company

Funding (last 2 of 7 rounds)

Jul 2021

$150m

SERIES D

Oct 2019

$110m

SERIES C

Total funding: $334m

Company benefits

  • Health Insurance
  • Mental Health Care
  • Accidental Death & Dismemberment Insurance
  • Dental Insurance
  • Disability Insurance
  • Flexible Spending Account (FSA)
  • Health Savings Account (HSA)
  • Life Insurance

Company values

  • Grit - We thrive outside of our comfort zone, pushing ourselves to go ever further. We think long-term and constantly strive to be better, even if things don't always go as expected
  • Trust - We trust each other just as we trust our users. We earn that trust by listening to each other, following through with our commitments and keeping our words
  • Care - We want the best for our customers, community & colleagues. We go above and beyond to make sure they are happy
  • Candor - We are open and honest. We give each other praise and criticism because we want to challenge each other and help one another grow
  • Humility - We want our teammates to succeed as much as we do ourselves. We believe each team member is as important as the other and we approach each new challenge knowing that we may not have all the answer

Company HQ

Barron Park, Palo Alto, CA

Leadership

Bernadette Nixon

(CEO, not founder)

Was previously CEO of Alfresco. Before that, was CRO at SDL and SVP & GM for OpenText


People progressing

Joined as an Account Executive. Promoted to Senior Account Executive after 1 year. They have been promoted to Director of Sales, Northern Europe.

Joined as an Enterprise Account Executive. Promoted to Director of Enterprise Sales after 2 years. Then promoted again to Head of Sales after 1 year. They are currently the Vice President of Sales for EMEA & APAC regions.

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