Lead Data Engineer

Role overview Lead the design and delivery of data engineering solutions across client projects. You will build and optimize pipelines, models, and integrations that make data reliable and useful for analytics, customer engagement, and business decisions, while providing technical direction to engineering peers. The role combines hands-on work with consulting responsibilities and collaboration across data, analytics, CRM, and customer data platform teams.

Responsibilities - Design and maintain scalable batch and real-time ETL/ELT pipelines. - Build and optimize data models, transformations, and workflows using SQL, Python, and dbt. - Integrate cloud data platforms, warehouses, and external data sources. - Improve performance, reliability, data quality, and operating costs through monitoring, validation, tests, and optimization. - Translate customer engagement needs into data models and pipelines, including event, identity, attribute, and synchronization use cases. - Advise engineers on technical practices, communicate recommendations to clients, and manage shifting priorities across engagements. - Identify useful applications of AI and automation in engineering workflows.

Requirements - At least five years in data engineering, data platforms, or a closely related role, with ownership of architecture and delivery. - Four or more years using SQL for data modeling and ETL/ELT work. - At least two years using Python for data applications or transformations. - Practical experience with dbt and modular transformations. - Experience with a major cloud provider and modern data integration tools. - Strong knowledge of data architecture, pipeline design, performance, testing, and data quality. - Ability to translate business needs into technical solutions and explain trade-offs clearly. - Consulting or agency experience handling multiple clients; strong English communication (C1 or equivalent).

Nice to have - Experience with Snowflake, Hightouch, mParticle, Databricks, BigQuery, or Redshift; a relevant advanced Snowflake certification is also valued. - Familiarity with customer data platforms, identity resolution, audience activation, real-time synchronization, CRM, or customer engagement data models. - Data visualization experience, governance and privacy knowledge, or exposure to AI/ML services and agent workflows. - Experience with Agile or Scrum.

Benefits and work setup - Remote-first work with an international team, career progression, and opportunities to take ownership. - Bring-your-own-device policy; applicants need existing work authorization in the hiring region, as sponsorship is unavailable.