Software Engineering Team Lead

At Corsearch, we are dedicated to creating a world where consumers can trust the choices they make.

As a global leader in Trademark and Brand Protection, we partner with businesses to safeguard their most valuable assets in an increasingly complex digital environment.

Our comprehensive solutions, powered by AI-driven data and deep analytics, enable brands to establish, monitor, and protect their presence against infringement and counterfeiting.

**Why Choose Corsearch?**
- ** Innovative Solutions**: We combine cutting-edge technology with expert judgment to deliver market-leading services in trademark clearance, brand protection, and anti-counterfeiting.
- **Global Impact**: Trusted by over 5,000 customers worldwide, including 73 of Fortune's Top 100 companies, our work has a meaningful impact on businesses and consumers alike.
- **Collaborative Culture**: With a team of over 1,900 professionals across multiple global offices, you'll be joining an inclusive environment where diverse perspectives thrive.
- **Mission-Driven Purpose**: Our commitment to protecting consumers and their trust in brands drives everything we do, making Corsearch a force for good in the world.

**The Role**

Corsearch is seeking a hands-on **Engineering Team Lead** to guide our **Analytics & Reporting** team within the broader Engineering function. This team is instrumental in delivering accurate, scalable, and insightful data products and solutions across the business — from standard and custom client reporting to internal analytics infrastructure.

We are looking for a **seasoned engineer** with a strong data mindset, ideally someone who has led highly effective technical teams, driven architectural decisions, and can code and contribute alongside their team.

A background with and eagerness for interfacing with product, engineering, and business teams will help you be successful in this highly collaborative, impact-focused role.

This is a **critical and exciting leadership position** in shaping the direction and development of our data reporting platform and infrastructure.

**Responsibilities and Duties**

**Shape a Unified Analytics Architecture**
- Lead the consolidation of existing data pipelines, warehouses, and BI layers — guiding technology selection, migration sequencing, and de‑duplication of overlapping datasets.
- Inform the future‑state reference architecture to deliver low‑latency, efficient, and highly governed analytics for our products and operations at scale.
- Build deep partnerships with other Engineering leads to align data models, event schemas, and retention strategies that work for both operational systems and analytical workloads.

**Lead & Grow a High‑Impact Team**
- Manage and mentor data engineers and data analysts, setting clear goals and coaching them through complex integration challenges.
- Cultivate a culture of ownership, experimentation, and continuous learning—where engineers feel safe to innovate and push boundaries.
- Drive hiring and career development in tandem with the VP of Engineering as the team expands.

**Assure Pipeline Reliability & Metric Integrity**
- Own end‑to‑end quality for batch and streaming pipelines that feed the consolidated lake‑house; codify SLAs/SLOs, automated testing, lineage, and alerting.
- Steward a canonical metrics layer—co‑designing models with Product, AI, and Finance so every dashboard speaks the same language.
- Triage and resolve data incidents fast, leading root‑cause analysis and systemic fixes.

**Facilitate Experimentation, Insights & Self‑Service**
- Oversee the evolution of standard client reports and bespoke data feeds, ensuring new reporting surfaces seamlessly as product teams ship features.
- Guide analysts in query performance tuning, semantic‑layer design, and visualization best practices.
- Evangelize data‑driven decision‑making by surfacing high‑value insights to Product, GTM, and Operations leaders.
- Own end‑to‑end quality for batch and streaming pipelines that feed the consolidated lake‑house; codify SLAs/SLOs, automated testing, lineage, and alerting.
- Steward a canonical metrics layer—co‑designing models with Product, AI, and Finance so every dashboard speaks the same language.
- Triage and resolve data incidents fast, leading root‑cause analysis and systemic fixes.

**Essential**
- Combined 6+ years in data or software engineering, data science, and analytics, 2+ years guiding teams through large‑scale platform migrations or consolidations.
- Proven mastery of SQL‑centric warehouses (e.g., Snowflake, ClickHouse, BigQuery) and modern data‑ops tooling (e.g., dbt, Airflow, Git‑based CI/CD).
- Track record of collaborating with Product and Engineering on data‑model design, metric development, event instrumentation, and release workflows.
- Fluency in Python and appreciation for software development tooling and best-practices (e.g., git, testing, local environments, CI/CD, etc.)
- Command of cloud architecture and infrastructure, including