Data Infra Tech Lead jobs at Melio in Israel, Tel Aviv-yafo

Qualifications:

• 5+ years of working experience as a Data Analyst in a startup organization, preferable fintech or within payments and/or finance
• Strong experience working with SQL
• Experience working with BI or Data Visualization platforms such as Tableau, Power BI, Looker etc.
• Demonstrated ability to analyze and extract actionable insights from large sets of data and experience utilizing and connecting information across multiple tools and softwares to produce a variety of reports
• Exceptional communication skills with the ability to work with senior management leading strategic cross-company projects, and liaising with global teams

Bonus points:

• B.S. in Computer Science, Statistic, Mathematics, or other relevant fields is preferred
• Experience working with Python a plus

A day in the life and how you’ll make an impact:

• Oversee the entire data, analytics, and BI scope across the domain - from building quarterly work plans, to managing and prioritizing day-to-day initiatives
• Own and deliver on complex analytical projects end-to-end including analytical design and execution, relevant asset development, and extracting objective and actionable insights for business recommendations
• Work collaboratively with leadership, partners, and operational teams throughout the domain to provide high-impact insights and evangelize data-driven decision making
• Develop and maintain data quality to ensure accurate and reliable reporting across the entire organization, while monitoring strict adherence to protocols and procedures for data hygiene
• Collaborate with the global Data Analytics team in Tel Aviv, to keep one source of truth and maintain a consistent methodology

About Melio USA:

• Competitive compensation packages: We strive to make each and every employee feel valued and appreciated.
• The annual base salary range for this position is $140,000-155,000
• Medical, Dental, and Vision: We offer generous and highly competitive plans with up to 100% employer-paid coverage, FSA and HSA.
• 401K matching and stock options: Feel the investment of working at a hyper-growth startup.
• Wellness: We take a holistic approach to wellness at Melio with a focus on providing financial, physical, emotional, social, and community support for our employees.
• Time Off: Time to rest and recharge is a priority for us. We offer competitive vacation time, sick days, holidays, parental leave and wedding days to allow you to take the time you need, when you need it.
• Food perks: Enjoy our fully stocked kitchens, along with a weekly Seamless stipend and plenty of catered meals each week.
• Office culture: Thrive in our collaborative offices in New York City or Denver, in a hybrid working environment. We are dog friendly as well!
• Growth and development: Lean on the diverse team to foster professional and personal growth through workshops, mentorship programs, and team building activities.

As a
Data Product Manager, you will architect and oversee robust data foundation systems that enable the organization to efficiently collect, process, store, and leverage data at scale. You'll lead the development of mission-critical data infrastructure products with company-wide impact, addressing complex technical challenges and designing solutions that enhance data accessibility, reliability, and innovation across the organization.

We're looking for someone with a proven track record in technical product management and deep expertise in data infrastructure technologies to build scalable, resilient, and innovative data platform solutions.

Qualifications:

• A proven track record of over 4 years in Product Management roles with a strong focus on data infrastructure products like storage systems, ETL frameworks, or data orchestration platforms, GenAI products.
• Data is your second (or first) language. You can read and explain stats and define metrics to anything you want to measure.
• Hands-on experience with data and good familiarity with data solutions and technologies
• You are passionate about solving complex technical issues around data scalability, reliability, and governance, with a keen understanding of how robust infrastructure enables downstream data applications."How" is your keyword. You're curious about system architectures and constantly looking for ways to improve efficiency, reliability, and maintainability.
• You can drive collaboration across multiple disciplines—data, design, finance, ops, engineering, etc. You help give everyone a voice. You’re the conductor, not the lead singer, and softly leading without forced authority is key.
• You're fluent in English with excellent speaking and writing skills.
• BS in computer science, engineering or equivalent experience.

How you'll make an impact:

• Develop and execute a data infrastructure roadmap aligned with the company's technical strategy, building scalable foundations that support both current and future data initiatives.
• Identify opportunities and collaborate with stakeholders to design and implement capabilities like data lineage tracking, automated data quality monitoring, and self-service infrastructure components.
• Define both business and technical requirements for new data infrastructure initiatives, write clear and concise architecture documents, technical specifications, and other product documentation.
• Collaborate with platform engineering teams to build, deploy and scale infrastructure components that enable reliable data operations.
• Act as the bridge between infrastructure teams and data consumers (analysts, data scientists, ML engineers) to ensure the platform meets evolving needs.
• Define and monitor platform KPIs to assess infrastructure performance, measure reliability, and prioritize enhancements for maximum organizational impact.

About The Product Department

We are user experts and constantly analyze their current and future needs. We define the product roadmap, including features and requirements, and then articulate the business rationale behind it. The team is responsible for providing the ‘what’ and working with the engineering team to build a successful product.

As a, you will play a central role in shaping our data strategy and guiding the team in building and optimizing analytics data pipelines that power business decisions across the organization. Beyond driving complex data initiatives, you’ll be a hands-on mentor and technical advisor, supporting other data engineers, fostering a culture of collaboration, and ensuring the team’s overall growth and success.

• Lead and mentor a team of data engineers, providing technical guidance, support, and regular feedback to enable their growth.
• Architect, design, and evolve robust, scalable data pipelines and ETL/ELT processes for diverse structured and unstructured data sources.
• Serve as a technical advisor for data best practices across the organization, collaborating with data analysts, data scientists, engineers, and product managers.
• Define and evolve analytics-focused data models that empower business stakeholders with timely and reliable data.
• Drive initiatives to improve data quality, governance, and observability across the analytics stack.
• Act as a bridge between technical and non-technical stakeholders, helping translate business needs into actionable data solutions.
• Champion engineering excellence, including code reviews, documentation, and knowledge-sharing.

• 7+ years of experience in data engineering or related roles, with a proven track record of technical leadership and team support.
• Expertise in SQL and advanced proficiency in Python for data workflows.
• Extensive experience designing and implementing scalable, analytics-ready data models and cloud data warehouses.
• Hands-on expertise with data orchestration and transformation frameworks (e.g., Airflow, Luigi, AWS Glue, DBT).
• Strong familiarity with cloud data services (e.g., AWS, GCP, Azure).
• Demonstrated ability to lead and support teams, communicate effectively, and foster collaboration across functions.

• Experience mentoring or managing engineers in a fast-paced environment.
• Strong understanding of business metrics and how to translate data into strategic insights.
• Familiarity with data governance and observability best practices.
• Passion for building data culture and driving adoption of data tools across the company.

• Leading the most complicated data projects Melio has to offer Hands on
• Supporting other engineers by reviewing code, troubleshooting architecture, and encouraging best practices.
• Leading the technical direction of new pipelines or data modeling initiatives.
• Meeting with product managers and analysts to align on priorities and define the right data solutions.
• Guiding your team through design discussions, trade-offs, and implementation decisions.
• Helping the team deliver with high reliability, scalability, and speed.
• Driving initiatives that improve the maintainability, observability, and impact of the data platform.

Qualifications:

• 7+ years of experience in data infra or backend engineering.
• Strong knowledge of data services architecture, and ML Ops.
• Experience with cloud-based data infrastructure in the cloud, such as AWS, GCP, or Azure.
• Deep experience with SQL and NoSQL databases.
• Experience with Data Warehouse technologies such as Snowflake and Databricks.
• Proficiency in backend programming languages like Python, NodeJS, or an equivalent.
• Proven leadership experience, including mentoring engineers and driving technical initiatives.
• Strong communication, collaboration, and stakeholder management skills.

Bonus Points:

• Experience leading teams working with serverless technologies like AWS Lambda.
• Hands-on experience with TypeScript in backend environments.
• Familiarity with Large Language Models (LLMs) and AI infrastructure.
• Experience building infrastructure for Data Science and Machine Learning.
• Experience collaborating with BI developers and analysts to drive business value.
• Expertise in administering and managing Databricks clusters.
• Experience with streaming technologies such as Amazon Kinesis and Apache Kafka.

A day in the life and how you’ll make an impact:

You will:

• Lead the design and development of scalable, reliable, and secure data storage, processing, and access systems.
• Define and drive best practices for CI/CD processes, ensuring seamless deployment and automation of data services.
• Oversee and optimize our machine learning platform for training, releasing, serving, and monitoring models in production.
• Own and develop the company-wide LLM infrastructure, enabling teams to efficiently build and deploy projects leveraging LLM capabilities.
• Own the company's feature store, ensuring high-quality, reusable, and consistent features for ML and analytics use cases.
• Architect and implement real-time event processing and data enrichment solutions, empowering teams with high-quality, real-time insights.
• Partner with cross-functional teams to integrate data and machine learning models into products and services.
• Ensure that our data systems are compliant with the data governance requirements of our customers and industry best practices.
• Mentor and guide engineers, fostering a culture of innovation, knowledge sharing, and continuous improvement.

About the hiring department:

Read more about our Engineering department

Minimum qualifications to apply for this role:

• 5+ years of experience as a Data Analyst
• SQL at a high level is mandatory
• An ability to understand complex ideas and simplify them to relevant stakeholders.
• Team player, effective interpersonal skills and good vibes. Manage relationships with key partners across different functions, ability to work independently
• Experience in fast-paced, high-intensity work environment
• Experience in BI tools such as Tableau, Redash or similar
• Experience in data modeling, ETL development, and data warehousing

Preferred qualifications (If you have those, we see it as advantage, but it's not a must)

• Experience in Python
• B.S in one of the following: Industrial Engineering, Statistics, Mathematics, Economics, or a related field.

How your day is going to look, what you will be doing?

- Helping each team to take decisions based on data by:

• Identify, analyze, and interpret trends or patterns in complex data sets to drive actionable insights
• Define and implement KPIs across different teams
• Accompany product features from tech design to feature performance
• Translate product/business requirements to analytical logics, and create a very clear visualization which "tells the story" using a BI tool or other platform.

As a Senior 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.

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:

• 5+ 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, Luigi, AWS Glue, DBT).
• Strong experience with cloud data services (e.g., AWS, GCP, Azure).
• 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
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker)
• 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

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.

As a Data Engineer, you will collaborate with various stakeholders to design, develop, and maintain data analytics solutions that enable informed business decisions. You will use the latest tools and technologies to ensure the data is accurate, timely, and actionable.

Qualifications:

• 3+ years of experience working as a BI Developer or Data Engineer
• Excellent SQL skills
• Python proficiency
• Experience designing analytics-oriented data models and data warehouses
• Experience working with data pipelines and ETL processes (e.g., Airflow, Luigi, AWS Glue, DBT)
• Passionate about data with a strong analytical approach
• Experience working with cloud environment services (e.g., AWS, GCP, Azure)

Bonus points:

• Strong understanding of business metrics and how to translate data into actionable insights
• Experience with data visualization tools (e.g., Tableau, Power BI, Looker)
• 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

How is your day going to look, what will you be doing?

• Develop data solutions in collaboration with data analysts, data scientists, product engineers, and product managers
• Design and develop the infrastructure for ingesting and processing data in the analytics data warehouse
• Design data analytics modeling solutions focused on business decision-making
• Write robust ETL processes, handling a variety of structured and unstructured data sources
• Ensure data quality, consistency, and governance across the analytics layer