Engineering Manager (Tech Lead Manager)
We're building a Data Quality, Observability & Governance Team to make Depop's data more reliable, trustworthy, and compliant.
As an Engineering Manager (Tech Lead Manager) for this team, you'll lead a group of engineers focused on improvingdata reliability, reducing time to detect and resolve data incidents, and driving accountability across data producers and consumers.
You'll provide both technical leadership and people management, helping define and execute the strategy for data observability, data contracts, and governance frameworks — ensuring our data is treated as a product: reliable, discoverable, high-quality, and built with clear ownership and accountability.
Your team's mission is to improve the mean time to detection and resolution (MTTD/MTTR) for data incidents, establish data contracts between producers and consumers, and embed GDPR and privacy-by-design principles into our data stack.
Responsibilities
- Lead and grow a multidisciplinary team of data and backend engineers focused on data quality, observability, and governance.
- Drive the technical direction for data observability tooling, incident management automation, and quality frameworks.
- Champion a "data as a product" culture, ensuring data producers own the quality, discoverability, and usability of their datasets.
- Define and roll out data ownership models, quality SLAs, and contracts aligned with product thinking.
- Collaborate with data platform, analytics, machine learning and product engineering teams to embed observability and validation throughout our data lifecycle.
- Partner closely with legal, compliance, and security teams to ensure GDPR and privacy-by-design are integrated into all systems.
- Define data reliability KPIs and build monitoring and alerting systems for proactive incident detection
- Recruit, mentor, and develop engineers; foster a team culture centred on accountability, learning, and craftsmanship.
- Balance hands-on technical work with coaching and strategic planning - setting clear goals, metrics, and delivery outcomes
- Represent the team in cross-functional forums, influencing technical direction across Depop's broader data ecosystem.
- Continuously improve team operations, emphasising automation, transparency, and measurable impact on data reliability.
Qualifications
- Proven experience as an Engineering Manager or Tech Lead Manager leading data or platform teams.
- Strong background in data engineering, observability, and distributed systems - ideally with prior hands-on experience in data infrastructure, reliability, or governance.
- Expertise in building or managing systems leveraging Databricks, Spark, Kafka, or Airflow, with a strong grasp of modern data stacks.
- Familiarity with data observability tools (Monte Carlo, Soda, etc.) and data validation frameworks (Great Expectations, DBT tests).
- Experience defining and managing data contracts, lineage, and metadata systems.
- Understanding of privacy regulations (GDPR, CCPA) and best practices for compliant data management.
- Strong belief in and experience applying data-as-a-product principles - driving quality, usability, and accountability across the data lifecycle.
- Strong people leadership skills: you know how to motivate, coach, and scale a high-performing technical team.
- Excellent communication and collaboration skills, with a proven ability to align technical direction across teams.
- Strategic and pragmatic thinker - able to define a long-term vision while delivering incremental value.
Bonus Points
- Experience building or managing data reliability or governance functions in a consumer or marketplace company.
- Prior success implementing automated data quality SLAs or self-healing data pipelines.
- Passion for treating data as a product - reliable, observable, and compliant by design.
Engineering Manager (Tech Lead Manager)
We're building a Data Quality, Observability & Governance Team to make Depop's data more reliable, trustworthy, and compliant.
As an Engineering Manager (Tech Lead Manager) for this team, you'll lead a group of engineers focused on improvingdata reliability, reducing time to detect and resolve data incidents, and driving accountability across data producers and consumers.
You'll provide both technical leadership and people management, helping define and execute the strategy for data observability, data contracts, and governance frameworks — ensuring our data is treated as a product: reliable, discoverable, high-quality, and built with clear ownership and accountability.
Your team's mission is to improve the mean time to detection and resolution (MTTD/MTTR) for data incidents, establish data contracts between producers and consumers, and embed GDPR and privacy-by-design principles into our data stack.
Responsibilities
- Lead and grow a multidisciplinary team of data and backend engineers focused on data quality, observability, and governance.
- Drive the technical direction for data observability tooling, incident management automation, and quality frameworks.
- Champion a "data as a product" culture, ensuring data producers own the quality, discoverability, and usability of their datasets.
- Define and roll out data ownership models, quality SLAs, and contracts aligned with product thinking.
- Collaborate with data platform, analytics, machine learning and product engineering teams to embed observability and validation throughout our data lifecycle.
- Partner closely with legal, compliance, and security teams to ensure GDPR and privacy-by-design are integrated into all systems.
- Define data reliability KPIs and build monitoring and alerting systems for proactive incident detection
- Recruit, mentor, and develop engineers; foster a team culture centred on accountability, learning, and craftsmanship.
- Balance hands-on technical work with coaching and strategic planning - setting clear goals, metrics, and delivery outcomes
- Represent the team in cross-functional forums, influencing technical direction across Depop's broader data ecosystem.
- Continuously improve team operations, emphasising automation, transparency, and measurable impact on data reliability.
Qualifications
- Proven experience as an Engineering Manager or Tech Lead Manager leading data or platform teams.
- Strong background in data engineering, observability, and distributed systems - ideally with prior hands-on experience in data infrastructure, reliability, or governance.
- Expertise in building or managing systems leveraging Databricks, Spark, Kafka, or Airflow, with a strong grasp of modern data stacks.
- Familiarity with data observability tools (Monte Carlo, Soda, etc.) and data validation frameworks (Great Expectations, DBT tests).
- Experience defining and managing data contracts, lineage, and metadata systems.
- Understanding of privacy regulations (GDPR, CCPA) and best practices for compliant data management.
- Strong belief in and experience applying data-as-a-product principles - driving quality, usability, and accountability across the data lifecycle.
- Strong people leadership skills: you know how to motivate, coach, and scale a high-performing technical team.
- Excellent communication and collaboration skills, with a proven ability to align technical direction across teams.
- Strategic and pragmatic thinker - able to define a long-term vision while delivering incremental value.
Bonus Points
- Experience building or managing data reliability or governance functions in a consumer or marketplace company.
- Prior success implementing automated data quality SLAs or self-healing data pipelines.
- Passion for treating data as a product - reliable, observable, and compliant by design.
