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Offer summary
(Summary generated by AI based on the full job description)
The project focuses on building an intelligent energy network connecting large-scale batteries at industrial sites. Key technologies include Python, ETL/ELT, PostgreSQL and work with time-series data on AWS. Responsibilities cover end-to-end management of data pipelines, ensuring data quality and monitoring, deploying ML models to production, and collaborating with external partners. The role demands experience with production ML systems and data and the ability to operate in imperfect information environments.
from: 7 July 2026
to: 6 August 2026
22 000 - 28 000 złnet (+ VAT)/ mth.B2B contract (full-time)
Salary details
basic salary
Offer parameters
level:mid
working mode:remote
Warszawa, Śródmieście
Requirements
Expected technologies
Python
PostgreSQL
SQL
AWS
ETL/ELT
Time-series data
Our requirements
- 3-6 years in data or ML engineering, or applied data science, with a clear track record of shipping to production and living with what you shipped
- Python fluency where clean, tested, production-grade code is your baseline, not your best day
- Hands-on with ETL/ELT pipelines, data modeling, and the specific quirks of time-series data
- Strong PostgreSQL, including schema design and query tuning under real load
- Treat data quality, validation, and monitoring as first-class engineering, not an afterthought
- Comfortable working close to the metal on AWS, without an abstraction layer doing the thinking for you
- Have run models and pipelines in production before, whether as APIs, batch jobs, or scheduled workflows
- Thrive in an early-stage setting: you scope pragmatically, make a call with imperfect information, and keep moving
- English - C1
Optional
- Exposure to energy markets, industrial systems, or hardware-adjacent data such as sensor streams and EMS integrations
- A foundation in forecasting, time-series analysis, or operations research
Your responsibilities
- Take end-to-end ownership of the data pipelines: ingest high-volume time-series feeds (telemetry, forecasts, energy market data) and make them clean, validated, and reliably available to everything downstream
- Build data quality in by default, with validation, anomaly detection, and monitoring wired into every pipeline rather than bolted on afterwards
- Shape the data platform architecture as it grows, balancing real-time responsiveness with heavy historical processing
- Partner with data scientists to take forecasting and optimization work from notebook to production, and stay on the hook for how those systems behave once they are live
- Push the quality of the modeling and algorithm work itself through code review, technical debate, and hands-on contribution, not just plumbing around it
- Embed data and models directly into the core product alongside the engineering team
- Own the data relationship with external partners (EMS providers, trading partners) so integrations stay clean at the source
About the project
Cyrantos is partnering with a fast-growing energy technology company to find a Data and ML Engineer to join their team. This is a remote position, with a start date as soon as the candidate successfully completes the interview process.
About the Role
As a Data and ML Engineer, you will take ownership of our client's data pipelines and bring advanced analytics and optimization models into production. The role sits at the intersection of data engineering, applied machine learning, and energy systems, bridging the data science and software engineering efforts.
Our client is building the energy company of the future: installing large-scale batteries at industrial sites and connecting them into an intelligent network that manages electricity in real time. This turns factories into energy hubs and makes intermittent renewables reliable, dispatchable, low-cost power around the clock. You will join an early-stage environment where the data platform is being built from scratch, scoping pragmatically and making opinionated decisions without waiting for perfect requirements.
This is how we organize our work
This is how we work
at the client's site
If you are a passionate Data and ML Engineer eager to help build the energy company of the future and grow within a dynamic team, we would love to hear from you.
Recruitment stages
- 1.Phone screening
- 2.Technical interview
- 3.Culture fit interview
Cyrantos - DevAbundance Sp. z o.o.
Cyrantos is a boutique partner for growing revenue by scaling tech teams, IT contracting, and specialized recruitment, trusted by enterprise organizations and fast-growing scale-ups across Europe. We help companies accelerate product development, strengthen engineering capabilities, and access vetted senior tech talent - quickly and transparently.
Born from a decade of experience building high-performance teams, Cyrantos was founded with a simple mission: deliver premium technical talent with honesty, speed, and deep business understanding. We’ve worked with 70+ clients, built 23 complete engineering teams, and placed 40+ specialists across software engineering, cloud, data, product, and leadership roles. Our approach blends a curated consultant network with rigorous vetting, allowing clients to onboard top performers without friction or lengthy recruitment cycles.
We believe in a partnership-first mindset: clear communication, transparent time reporting, and solutions tailored to every company’s stage of growth. Whether you’re augmenting your existing engineering team, building a product squad from scratch, or bridging hiring gaps with experienced contractors, Cyrantos ensures you scale efficiently and without compromise on quality.
Headquartered in Poland and operating internationally, we support clients across technology, finance, manufacturing, energy, gaming, and high-growth SaaS. Our commitment is to deliver exceptional people who not only bring technical expertise, but also strengthen culture, ownership, and delivery performance.
Data and ML Engineer
22k–28k zł / mth. (B2B)
I apply to:
Cyrantos - DevAbundance Sp. z o.o.
Warszawa, Śródmieście
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