Lead Data Engineer 2026- US, COL, UK
Lead client data engineering engagements by designing AI-ready data platforms, production pipelines, and semantic layers that enable analytics, natural-language querying, and AI-powered workflows.
Join a data infrastructure and analytics team building a platform that turns information from many sources into reliable company intelligence. You will own the platform end to end, from architecture and ingestion through production operations, helping deliver trusted data for downstream products.
Design and build a multi-source data platform for concurrent ingestion, event-driven processing, and orchestrated batch workflows.
Ingest data from provider APIs, webhooks, files, and web scraping, with rate limits and robust failure handling.
Orchestrate scheduled workflows and historical backfills with tools such as Airflow, Dagster, or Prefect.
Build event-driven systems with messaging or task queues, including retries, dead-letter queues, and controlled replay.
Store original payloads in cloud storage and transform data with dbt into raw, standardized, and curated layers.
Implement idempotent upserts, data contracts, validation, pipeline tests, and monitoring for freshness and failures.
Design and optimize PostgreSQL schemas and loading patterns, and integrate enrichment and LLM-based structured extraction.
At least 5 years building and operating production data platforms that ingest from multiple sources, with ownership from architecture through deployment and ongoing operations.
Production experience with workflow orchestration, including dependencies, retries, and failure recovery. Airflow is preferred; Dagster, Prefect, Temporal, or comparable tools also count.
Hands-on production experience with dbt and Google Cloud Platform.
Strong Python skills, including asynchronous HTTP and concurrent processing with tools such as asyncio, aiohttp, or HTTPX.
Strong SQL and PostgreSQL skills, including data modeling, query optimization, and incremental loading.
Experience building event-driven systems and implementing data contracts, retention policies, validation, testing, and monitoring.
Experience building platforms or substantial pipelines from scratch is valued. Web scraping, entity resolution, enrichment, and early-stage team experience are also helpful.
Salary range: $100,000 to $140,000 USD annually. Visa sponsorship is not available.
Remote within Europe, including the United Kingdom, Norway, Switzerland, Ukraine, Iceland, and Liechtenstein.
Lead client data engineering engagements by designing AI-ready data platforms, production pipelines, and semantic layers that enable analytics, natural-language querying, and AI-powered workflows.
Build and improve a scalable data platform and tools that support analytics, machine learning, and AI products, including semantic-layer and LLM-powered data capabilities.
Design and implement governed data solutions using Databricks, Unity Catalog, and medallion architecture, shaping scalable data designs, metadata standards, access controls, and production pipelines.
Design, automate, and secure scalable AWS data platforms, owning infrastructure, data workflows, CI/CD, and cloud security while improving reliability, performance, compliance, and operational efficiency.
Desenvolva e otimize pipelines e arquiteturas Lakehouse, integrando dados corporativos e preparando informaรงรตes confiรกveis para soluรงรตes de analytics, IA conversacional, assistentes virtuais e agentes inteligentes.