Analytics Engineering Manager
As part of a goal to make the Data, Research & Insight (DRI) function fit for an AI-powered future, the Analytics Engineering Manager will be the primary lead for data enablement within the Insight Products team. The core purpose is to ensure that high-quality, well-governed data is available for use by the Insight Products team and their stakeholders.
Direct Reports: 3 Technical Business Analysts, 2 Analytics Engineers.
Measures of Success
- Data Trust: significantly improved organizational confidence in data through superior governance, observability, and documentation.
- Seamless Collaboration: effective working relationship with the Business Intelligence Manager and central Data Engineering to maintain a robust data supply chain.
- Community Support: technical foundation that allows decentralized users to successfully self-serve.
- Delivery Velocity: demonstrable reduction in time-to-market for new data products, super-charged by AI-assisted development and design-by-building methodologies.
- Data Reliability: consistently meeting or exceeding defined SLAs for data quality, availability, and documentation.
- Self-Serve Ratio: increase in the ratio of automated self-serve usage compared to bespoke manual data requests.
- Observability Metrics: achievement of targets for data anomaly alerting and resolution times.
Responsibilities
- Lead and mentor a team of Technical BAs and Analytics Engineers, fostering a culture of excellence, full-stack mindsets, and AI-powered efficiency.
- Work with the Insight Products Director and stakeholders to prioritise and define high-quality requirements for the central Data Engineering team.
- Oversee and execute internal data engineering tasks, including building data pipelines, tables, views, instrumentation, and tagging.
- Act as a technical consultant and partner to the BI Manager in the development of conversational interfaces (Analytics Agents), custom UIs, and analytics apps.
- Establish and maintain rigorous data documentation, catalogs, and observability processes (e.g., anomaly alerting) to ensure data is discoverable and reliable.
- Lead efforts in third-party data enhancement and the curation of unstructured data to enable broader self-serve analytics.
Who You Are
- Analytics Engineering mastery: deep technical expertise in modern analytics engineering workflows (SQL, Python, dbt, Snowflake, or BigQuery) and data modelling.
- Technical Business Analysis: proven track record in gathering complex technical requirements and translating them into scalable data solutions.
- People Leadership: experience managing or supervising data/engineering professionals and history of leading high-performance teams.
- Focus on Pace: success of the function depends on pace to deliver reusable and robust data assets.
- Culture: demonstrable track record of nurturing and training talent and creating a culture of excellence, ownership, agency, learning and innovation.
- Software Engineering Basics: familiarity with version control, CI/CD to support blurring lines between data and application development.
- Modern Data Stack: recent experience with tools such as Snowflake, Amplitude, Monte Carlo, or Google Analytics.
- Change Management: experience working through organizational re-designs or function-wide transformations.
- Innovation with Impact: track record of technical and process innovation that delivers impact beyond POCs.
Desirable
- Emerging Tech (AI/LLM): experience building or deploying AI-powered agents, conversational interfaces, or leveraging LLMs for data discovery.
- Data Governance: hands‑on experience with data documentation, quality monitoring tools, and establishing data catalogues.
Working Arrangements
The majority of our roles operate on a hybrid working pattern, with 3 or more days office attendance required.
What We Offer
Our benefits package is designed to support your wellbeing, growth, and work-life balance. It includes a highly competitive pension or 401(k) plan, private health insurance, and continuous access to counseling and wellbeing resources through our Employee Assistance Program.
We also offer lifestyle benefits, including a Work From Anywhere program, which allows you to work from any location where you have the legal right to do so for up to 25 days per year. In addition, we provide generous annual and parental leave, and dedicated days off for volunteering and moving home.
You will also be given free access to all The Economist content, including an online subscription, our range of apps, podcasts and more.
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