Data Engineer for data processing
Required technologies
Job description
We are looking for a mid Data Engineer for data processing with expertise in Data and proficiency in Data-Engineer, Data-SCIence, Python, Kafka.
We offer a full-time position with a salary ranging from 2,947 to 3,929 EUR.
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About Company Millennials Agency
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Pre-apply checklist
Quickly verify the listing has the essentials so you can compare offers fairly.
- Is the salary gross or net, and what period is it for?
- Is it employee (CIM) or contractor (B2B/PFA/SRL)?
- What does “remote/hybrid” mean in practice (office days, overlap)?
- Is the scope and seniority level clear?
Flag missing or inconsistent details so the listing stays accurate.
How to apply
This position requires direct contact with Millennials Agency for application details.
How to evaluate this job (beyond the title)
A strong application is not just “I know the stack”. It’s proof you can deliver outcomes in this specific context: team setup, constraints, seniority expectations, and the way success is measured. Use this checklist to decide whether to apply and what to highlight.
Clarify scope and expectations
Many ads are intentionally broad. Your job is to identify the core responsibilities and whether they match your strengths today.
- Look for ownership signals: “design”, “architecture”, “lead”, “on-call”, “mentoring”.
- Check if the role is feature delivery vs platform/infra vs maintenance.
- If the description is short, use company size + industry + stack to infer the likely day-to-day.
Validate work setup and collaboration
Remote/hybrid/office labels are not enough. The real constraints are overlap hours, office days, and communication style.
- Confirm whether “remote” is worldwide/EU/Romania-only and whether overlap hours are required.
- For hybrid roles, ask how many days per week and whether they are fixed or flexible.
- Check language requirements and cross-team dependencies (product, design, stakeholders).
Compare compensation realistically
To compare two offers, normalize everything to the same baseline and contract type. If salary is undisclosed, build a range based on market and validate early.
- Normalize gross vs net and month vs year before you compare.
- For B2B, account for taxes, accounting, unpaid time off, and risk.
- Use market data as a sanity check, then negotiate with evidence (impact, scope, seniority).
Useful links for your decision
These pages help you sanity-check salary ranges and contract choices (especially when switching between employment and B2B).
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