Dropbox25 days ago

Старший менеджер по инженерии данных

Salary not specified

MARKET

15,667 ₽median for this role

Data Engineer · 11 jobs with disclosed pay

10,833half of the offers: 14,166–16,81220,833

The employer didn't disclose pay — compare with the market yourself.

Remote - US: Select locations

Responsibilities

01Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics
02Lead the engineering of the self-serve analytics substrate, reducing bespoke request volume and increasing partner-team autonomy
03Own the unit economics of the data platform — compute and storage efficiency — and drive measurable improvements without sacrificing reliability
04Partner deeply with Data Science, BIE, Analytics, Product, Data Platform, and the CTO org to define the semantic layer, modeling standards, and data contracts that make downstream work trustworthy and fast
05Establish rigorous engineering practices — code review, testing, CI/CD for data, incident response, and postmortems — and champion the effective, measured use of AI coding tools to improve engineering productivity
06Lead, mentor, and grow a high-talent-density team of data engineers, fostering a culture of ownership, technical excellence, psychological safety, and continuous learning

018+ years of data engineering or backend/data infrastructure experience with increasing scope, ideally in high-scale environments
023+ years of experience directly managing and growing engineering teams, including hiring, coaching, performance management, and team design
03Deep Technical Expertise: Proven track record building and operating large-scale batch and streaming pipelines (e.g., Spark, dbt, Airflow/orchestration) on a modern lakehouse or warehouse stack (e.g., Databricks, Snowflake, BigQuery)
04Reliability & Quality: Demonstrated ownership of data SLAs, observability, lineage, and incident response for business-critical pipelines
05Systems & Modeling: Strong data modeling fundamentals and the ability to design a semantic layer and data contracts that serve many downstream consumers
06Stakeholder Management: Excellent communication and the ability to align engineering, data science, analytics, and business partners around shared reliability and quality goals