Senior Engineer Manager

3 weeks ago

London, United Kingdom Algolia Full time

Algolia is looking for a Senior Manager to lead a team of Analytics Engineers, who work at the intersection of Business Teams, Data Analytics, and Data Engineering. You will be responsible for bringing robust, efficient, and integrated data models and analytical reports to life. Our Analytics Engineers speak the language of business teams and technical teams, they are able to translate data insights and analysis needs into models powered by Algolia’s Data Platform.
You will work closely together with the Senior Manager, Data Engineering Team who have a particular focus on data movement and orchestration. This with an analytical and business-oriented mindset with the ability to implement rigorous database solutions and best practices in order to produce and influence the adoption of strong quality data insights to drive business decisions in all areas of Algolia.
We currently use Redshift as our data warehouse. 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 with 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, Data Governance and Data Documentation best practices, measures, and remediation to help ensure all decisions are made using the best data possible.
Manage a team of 4 people, and are responsible to attract, retain, and develop deep technical talent by establishing Individual Contributor career paths for your team members who do not want to move into Data People Management.
Own one or more stakeholder relationships in Marketing Ops, Sales Ops, Product, Engineering, Customer Success, R&D Ops, Growth, and Finance.
Serve as Data Modeling subject matter expert and spokesperson for our data platform, demonstrated by the ability to address questions quickly and accurately.
Advocate for the Data Quality Program and Trusted Data to help ensure all data is profiled, reviewed, and accurate to support critical decisions.
Review and improve the data system as a whole, inclusive of data model designs, DAG designs, and end-use cases
Organize and Plan multi-quarter initiatives and develop the Analytics Engineering Roadmap
Set data architecture principles, standards, and guidelines
Continuously review current data modeling principles and initiate any improvements to enable the implementation of the intended architecture
Create an inventory of the data and tools needed to implement a scalable data architecture.
As a team lead responsible for helping to bridge the gap between business and technology, the Senior Manager, Analytics Engineering role requires equal amounts of business acumen and technical acumen.
Collaborate with team members to collect business requirements, define successful analytics outcomes, and design data models
Build trust in all interactions and with Trusted Data that has been tested, documented, and verified by our team and stakeholders.
Provide data modeling expertise through code reviews, pairing, and training to help deliver optimal and scalable database designs and queries
Maintain the Data Catalog, a scalable resource to support Self-Service and Single-source-of-truth analytics
Implement a developer's mindset to build data models: modular, unit-tested, documented.
Guide work to completion from high-level roadmaps to tactical project plans to sprint planning.
Identify and resolve impediments to efficiency and enable the entire Data Program to iterate faster
Bachelor's or Master’s degree in a technical discipline; Ability to thrive in a fully remote organization
~ Marketing Ops, Sales Ops, Product Engineering Ops, Customer Support, and Finance.
~6+ years in the Data space as a data analyst, analytics engineer, data scientist, or equivalent
~3+ years managing the same data model system over time, evolving the model to meet new business requirements
~2+ years managing an analytics engineering team using a scrum/agile methodology
~ Experience working with commercial data warehouses (Redshift), ETL tools (Dbt), data visualization (Python notebook, Thoughtspot, Looker, Tableau, Hex), and Data Dictionary tools (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 introducing a new software, tool, or technique to a multi-person team, leading to measurable productivity improvement
~ Experience with data access, administration, and security techniques, both inside and outside of a data warehouse
~ Experience with data pipelines in support of near real-time event stream processing
~ LI-Remote
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