Engineering Manager, Data

November 26

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AgencyAnalytics

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SaaS • Marketing • B2B

AgencyAnalytics is a software platform designed for marketing agencies to automate their client reporting. It offers a suite of tools including custom dashboards, automated reports, and over 80 integrations with popular marketing and analytics platforms. With its white-labeling capabilities, agencies can brand the reports as their own. The platform aims to improve efficiency and client satisfaction by centralizing marketing data and providing AI-driven insights. AgencyAnalytics is trusted by over 7,000 agencies worldwide for its ease of use and comprehensive features.

51 - 200 employees

Founded 2016

☁️ SaaS

🤝 B2B

📋 Description

• Lead, coach and grow a team responsible for data ingestion, transformations, integration connectors, and data warehouse. • Be a hands-on manager: split time between people management and technical work (architecture, code reviews, system design, and occasionally shipping code yourself). • Own delivery and outcomes for pipeline/integration and data warehouse projects. Set priorities with Product, remove blockers, and protect engineering focus. • Design and evolve reliable, observable, and secure data pipelines, data schemas, and integrations. • Drive best practices for data quality, schema evolution, idempotency, retries, backfills, and monitoring/alerting. • Collaborate with AI focused teams and Platform teams to design data contracts and interfaces that enable analytics and AI experiences (feature stores, embeddings, semantic indices). • Make architectural decisions with an eye toward scale, operability, cost, and maintainability; partner closely with Staff engineers on long-term architectural work. • Recruit, mentor, and develop engineers, helping them grow technically and in their careers. • Establish SLOs/SLIs for pipeline reliability, latency, and throughput; lead team incident response measures and postmortems.

🎯 Requirements

• Experience running a data pipelines / integrations team (ownership of ingestion, ETL/ELT, or connector platforms) • At least 1 year in an Engineering Manager role. Prior technical leadership (Tech Lead, Staff Engineer) is strongly preferred. • Familiarity with cloud data warehousing and analytics platforms (BigQuery), strong operational experience with relational databases (MySQL, Postgres), and caching systems (Redis). • Experience with API-first connector platforms and SaaS integrations. • Recent experience building data context for AI apps: feature stores, embeddings, vector DBs, semantic layers, or tooling that prepares data for LLMs and retrieval-augmented generation is a big plus. • Strong track record of delivering data systems that are reliable, observable, and maintainable. • Proven ability to manage tradeoffs between speed, correctness, and cost at scale. • Comfortable writing and reviewing production SQL, performing database tuning, migrations, and schema design. You want to stay technical.

🏖️ Benefits

• Health insurance • Retirement plans • Paid time off • Professional development • Flexible work arrangements