דרושים » דאטה » Financial Data Engineer

We are looking a highly skilled and motivated Senior Data Engineer to join our dynamic team.
The ideal candidate will be a great team player that can lead and also be responsible for designing, developing, and maintaining robust data pipelines and analytical solutions to support our business objectives.
This role requires a blend of engineering and analytical skills to ensure data integrity, optimize data workflows, and provide actionable insights.
This role requires a deep understanding of financial data, system integration, and analytics to support strategic decision-making and regulatory compliance.
Your Day-to-Day:
Design, develop, and maintain scalable data pipelines and ETL processes.
Collaborate with product, analysts, and other stakeholders to understand data requirements and translate business needs into technical requirements.
Ensure data quality and integrity across various data sources.
Develop, maintain and own data models, schemas, and documentation.
Optimize database performance and troubleshoot issues.
Stay updated with the latest industry trends and best practices in data engineering and analytics.

We are looking for a Senior Data Engineer.
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

Were looking for a Data Engineer to join our data warehouse team and play a pivotal role in driving data solutions that empower data science, GTM, finance, analytics and R&D teams.

If youre passionate about exploring and exposing product and business data to stakeholders across and beyond, wed love to hear from you.



What youll do:

Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements.
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs.
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into a shared data warehouse.
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency.
Collaborate with cross-functional teams (product, finance, analytics, and R&D) to deliver actionable data solutions tailored to their needs.

We are growing and are looking for a Senior Data Infra Engineer
who value personal and career growth, team-work, and winning!
What your day will look like:
Design, plan, and build all aspects of the platforms data, machine learning (ML) pipelines, and infrastructure.
Build and optimize an AWS-based Data Lake using best practices in cloud architecture, data partitioning, metadata management, and security to support enterprise-scale data operations.
Collaborate with engineers, data analysts, data scientists, and other stakeholders to understand data needs.
Solve challenging data integration problems, utilizing optimal ETL/ELT patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
Lead end-to-end data projects from infrastructure design to production monitoring.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructuresomeone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacksits about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakesdesigned for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Mentor, support, and guide junior team members, sharing expertise and fostering their professional development.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply and be responsible for best practices in data security, integrity, and performance across all systems.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply best practices for data security, integrity, and performance across all systems.

We are looking for a Senior Data Scientist (Applied AI).
As a Senior Data Scientist on our Applied AI team, you will join our Tel Aviv office and play a hands-on, end-to-end role in delivering innovative capabilities that help mayors and other city leaders understand their communities and improve the lives of millions worldwide. Reporting to the Applied AI Team Lead, you will collaborate with product, engineering, and fellow data-science teammates to turn cutting-edge research into production-ready solutionsquickly, reliably, and with maximum real-world impact. Youll work with a rich mix of data sources (including social media, news stories, survey results, resident feedback, and more) to create models and AI-powered features that scale.
Day to Day:
Design, build, and deploy AI and machine-learning solutions, from data exploration through modeling, evaluation, and integration into customer-facing products and internal tools.
Optimize models for quality and scalability through feature engineering, hyper-parameter tuning, runtime profiling, and thoughtful architectural choices.
Build and maintain data pipelines using tools such as Airflow, Spark, and Databricks to ensure clean, reliable inputs for downstream models.
Collaborate closely with product managers, engineers, and designers to refine problem statements, iterate rapidly, and ship impactful features on schedule.
Champion technical excellence by conducting code reviews, sharing best practices, and mentoring teammates across data science and engineering.
Stay current with the latest developments in AI-including LLMs, RAG systems, and AI agents-and proactively propose ways to incorporate new techniques into our workflows.
Work an in-person or hybrid schedule, spending at least three days per week in our Tel Aviv office.

We are looking for our first dedicated Data Engineer a self-motivated and proactive professional with a strong can-do attitude and a sense of ownership. This role involves taking responsibility across all data domains within the company, working closely with our analytics and development teams to build and maintain the data infrastructure that supports business needs. This position is ideal for someone ready to independently lead data engineering efforts and make a meaningful impact.

Responsibilities:
Design, develop, and maintain scalable data pipelines and ETL workflows using tools such as Python, dbt, and Airflow.
Architect and optimize our data warehouse to support efficient analytics, reporting, and business intelligence at scale.
Model and structure data from multiple internal and external sources (such as Salesforce, Jira, Mixpanel, etc.) into clean, reliable, and analytics-ready datasets.
Collaborate closely with our systems architect, analytics, and development teams to translate business requirements into robust and efficient technical data solutions.
Monitor and optimize pipeline performance to ensure data completeness and scalability.
Serve as a key partner and subject-matter expert on all data-related topics within the team.
Implement data quality checks, anomaly detection and validation processes to ensure data reliability.