Senior Data Engineer

Experience

6+ years

Core Skills

Snowflake, Airflow, AWS

Candidate’s location

LATAM, Europe

Work Model

Remote

Engagement

Full-time, long-term

English

Upper-Intermediate+

This is a Senior Data Engineer role with real ownership. You’ll lead the data pipelines and analytics foundation of an AI platform that helps companies manage their energy and carbon portfolios.

About the client

Our client is building an AI-enabled platform for energy portfolios. It helps organizations make sense of their energy use and carbon footprint across complex, multi-site portfolios, and turn that data into decisions.

The product brings together data from many sources into one place. That combined data powers the core application, portfolio analytics and a growing set of AI-driven features.

Your impact

You’ll own the client’s data platform through a critical delivery phase and make the early-2027 launch possible on the data side. Your work is to turn varied, messy client data into a reliable, well-modeled foundation that product, analytics and AI can trust. The standards you set for how data is ingested, tested and documented will shape the platform for years to come. Along the way, you’ll bring an AI-native way of working into the data workflow, from daily development all the way to CI/CD.

What makes you a great fit

Senior-level data engineering experience, including owning production pipeline design end to end as an autonomous individual contributor
Production ingestion pipelines from APIs, files and shared-data sources, orchestrated with Airflow, Dagster, Step Functions or similar
Hands-on production experience with Snowflake or another cloud data warehouse
Strong SQL and production-level Python
Experience with AWS, plus PostgreSQL
Daily use of agentic AI coding tools (e.g., Claude Code, Cursor) and experience scaling shared AI workflows into CI/CD
Comfortable with ambiguity and undocumented systems, and with making sound technical decisions without hand-holding
Strong English and clear communication with product and analytics stakeholders

Nice to have

Preparing data for AI/LLM use: semantic layers, metadata, retrieval-ready datasets
Hands-on with Terraform or other infrastructure-as-code tools
Experience with dbt, Databricks, Delta Sharing
Background in energy, utilities or sustainability data

What you will do

Architect, build and maintain ingestion pipelines that feed both the application and analytics
Design layered, well-modeled tables, from raw to analytics-ready, with clean schemas
Onboard client data from varied sources (e.g., Databricks via Delta Sharing) and integrate it with existing services
Make pipelines reliable and automated with data quality tests, monitoring, safe reprocessing and schema-change handling
Build a documented, tested data foundation for the app, analytics and future AI use cases
Work with product teams to define technical criteria and translate them into data solutions

Perks & Benefits

Competitive salary with regular reviews
Vacation (up to 20 working days)
Sick leave (10 working days)
National holidays as time off
Flexible working schedule, remote format
Direct cooperation with the customer
Dynamic environment with a low level of bureaucracy and great team spirit
Challenging projects in diverse business domains and a variety of tech stacks
Communication with top/senior-level specialists to strengthen your hard skills
Online team-building events

We welcome applicants of every background, identity, and life experience. If you’re excited about this role but don’t check every box, we’d still like to hear from you.

Sounds like a match? Apply now and let’s build something great together.

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