Data Engineer
Melio is hiring a Data Engineer in Tel Aviv, Israel. Level rates it ; you can apply on Melio.
Level's read on this job
- Uses AI ●●○○ is how Level rates this data engineer role: an ordinary role that requires AI tools.
- The posting mentions Claude, Snowflake and Airflow among its tools and skills.
- Level classes it as a senior role.
- Melio has 22 other open roles on Level.
- Posted in the last few days.
AI in this role
Design and optimize scalable data analytics pipelines using modern cloud infrastructure while leveraging AI coding assistants for daily engineering tasks.
As a Data Engineer, you will play a key role in shaping and driving our analytics data pipelines and solutions to empower business insights and decisions. Collaborating with a variety of stakeholders, you will design, develop, and optimize scalable, high-performance data analytics infrastructures using modern tools and technologies. Your work will ensure data is accurate, timely, and actionable for critical decision-making.
Our data platform is built on Snowflake as the analytics warehouse, with Airflow orchestrating our SQL and Python pipelines. We ingest data through Fivetran and S3-based Snowpipe, manage our infrastructure as code with Terraform on AWS, and monitor data quality with Monte Carlo and Snowflake native DQ. AI is part of how we work: we use Claude to speed up development, validation, and on-call triage across the stack.
Key Responsibilities:
- Lead the design, development, and maintenance of robust data pipelines and ETL processes, handling diverse structured and unstructured data sources..
- Collaborate with data analysts, data scientists, product engineers and product managers to deliver impactful data solutions..
- Architect and maintain the infrastructure for ingesting, processing, and managing data in the analytics data warehouse..
- Develop and optimize analytics-oriented data models to support business decision-making..
- Champion data quality, consistency, and governance across the analytics layer..
Qualifications:
- 3+ years of experience as a Data Engineer or in a similar role..
- Expertise in SQL and proficiency in Python for data engineering tasks..
- Proven experience designing and implementing analytics-focused data models and warehouses..
- Hands-on experience with data pipelines and ETL/ELT frameworks (e.g. Airflow, DBT, etc.)..
- Strong experience with cloud data services (e.g., AWS, GCP, Azure)..
- AI proficiency: hands-on experience using AI coding assistants such as Claude as part of your daily engineering workflow. You will use them to explore code, build and validate pipeline changes, triage incidents, and open pull requests. You know how to guide AI effectively, review its output critically, and own the quality of what ships..
- A deep passion for data and a strong analytical mindset with attention to detail.
Bonus points:
- Strong understanding of business metrics and how to translate data into actionable insights.
- Familiarity with data governance and data quality best practices.
- Excellent communication skills to work with cross-functional teams including data analysts, data scientists, and product managers.
- Familiarity with Terraform and infrastructure-as-code practices.
What your day might look like:
- Leading the design and implementation of scalable data pipelines to support analytical workloads..
- Collaborating with stakeholders to gather requirements, propose solutions, and align on data strategies..
- Writing and optimizing ETL processes to ensure seamless integration of new data sources..
- Designing analytics-focused data modeling solutions tailored for strategic decision-making..
- Troubleshooting data issues and implementing measures to improve system reliability and accuracy..
- Sharing knowledge and mentoring team members to promote a culture of learning and excellence.
This is an opportunity to make a significant impact by enabling data-driven decision-making at scale while growing your career in a dynamic, collaborative environment.
About the Engineering department:
The Engineering department is the backbone of Melio. We build, scale, and maintain the technical infrastructure that processes over $100B in annual payments for small businesses nationwide.
Following our acquisition by Xero, we’re tackling an even more exciting challenge: integrating Melio’s payment platform with Xero’s accounting software to create a unified financial ecosystem. This means building robust, scalable systems that seamlessly connect two powerful platforms while maintaining the security and reliability that financial services demand.
Our Stack:
We're all-in on AWS Serverless—meaning fully managed infrastructure that lets us build and scale faster than ever. We use TypeScript and Python for consistency, combining relational and document databases, and deploy via SAM CLI built on CloudFormation. Serverless gives us the agility to innovate rapidly while maintaining enterprise-grade reliability.
As part of our engineering team, you'll work on problems that matter: real-time payment processing, fraud prevention, API integrations, data synchronization, and user experience optimization. You'll have the autonomy to make architectural decisions, the support of a world-class team, and the satisfaction of seeing your code impact millions of small businesses.
If you're ready to build systems that scale, solve hard problems, and help small businesses thrive, we want to talk to you.
Read more about our Engineering department on our tech blog.
About Melio:
Melio, a Xero company, is revolutionizing how small businesses handle payments. By combining Melio’s best-in-class bill pay platform with Xero’s global accounting expertise, we’re building the ultimate financial command center for American small businesses. We’re the fastest-growing B2B payment solution in the US—but we’re still small enough that you can make real, visible impact as we scale to reach millions more businesses.
How we rate this
Data Engineer at Melio rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- What's a project where you used Claude hands-on?
- Walk me through how you've used Snowflake in your day-to-day work.
- What are the limits of Airflow that you've run into, and how did you work around them?
- What's a project where you used Python hands-on?
- Walk me through how you've used SQL in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Claude, Snowflake, Airflow, Python, and SQL. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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