Senior Data Engineer

NCube Ltd.; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

NCube Ltd. is recruiting a Senior Data Engineer to own the data platform and lead ingestion pipelines for an AI-enabled energy analytics platform. You will shape the data foundation across multi-site energy portfolios, enabling product, analytics and AI to trust and utilize the data.

You’ll design scalable data models, implement reliable ETL pipelines, and collaborate with product and analytics stakeholders to drive impactful data solutions in a fast-paced, ambiguity-rich environment.

Qualifications

• Senior-level data engineering with end-to-end pipeline ownership.
• Production ingestion pipelines from APIs/files/shared sources with orchestration.
• Experience with a cloud data warehouse (Snowflake or equivalent).
• Strong SQL and production Python skills.
• Experience with AWS and PostgreSQL.
• Familiarity with AI-enabled workflows and CI/CD.

Responsibilities

• Architect, build and maintain ingestion pipelines for app and analytics.
• Design layered, well-modeled tables from raw to analytics-ready.
• Onboard client data from varied sources and integrate with services.
• Make pipelines reliable with data quality tests and monitoring.
• Document and test the data foundation for app, analytics and AI use cases.
• Collaborate with product teams to define data criteria.

Skills

Data engineering

Pipeline design

SQL

Python

AWS

CI/CD for AI

Communication

Ambiguity tolerance

Tools

Snowflake

Airflow

Dagster

Databricks

Delta Sharing

Terraform

Job description

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

• 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
• Competitive salary with regular reviews
• Vacation (up to 20 working days)
• Sick leave (10 working days)
• National holidays as time off
• 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.