דרושים » תוכנה » Data Platform Engineer

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.

We are growing and are looking for a Senior Data Platform 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 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.

A fast-growing, well-funded startup in the data domain is looking for a Software Development Team Lead to lead a team of engineers, reporting to the Director of Engineering. As a Software Development Team Lead, you’ll lead a team of back-end, full-stack, and data engineers, working closely with Product Managers and other stakeholders to plan, kickoff, and execute new product and feature development projects. Our ideal candidate is someone who values excellence, is hungry for success, and thrives when working with the best. Job Summary: As an Software Development Team Lead, you'll be responsible for overseeing the design, development, and implementation of robust software solutions, including strategic full-stack applications and our big data architecture. You'll lead a team of engineers and collaborate with cross-functional teams to drive initiatives that support business objectives. Your expertise in big data technologies, including Elastic, Kafka, and Java, will be critical in ensuring the scalability and performance of our systems. What you’ll do:
? Lead and mentor a team of engineers in the design and development of software solutions, including big data solutions and full-stack applications. ? Architect and implement data processing pipelines ? real-time data streaming. ? Optimize and manage search capabilities. ? Develop strategic full-stack applications to meet business needs. ? Collaborate with product managers, data analysts, and other stakeholders to gather requirements and translate them into technical specifications. ? Oversee code reviews, ensure best practices in coding and data handling, and maintain high-quality standards in software development. ? Stay up-to-date with emerging trends and technologies in software engineering and big data, and recommend improvements to our architecture and processes. ? Troubleshoot and resolve issues in a timely manner to minimize downtime and ensure system reliability. ? Contribute to strategic planning and decision-making regarding architecture and tools. ? Collect and analyze your team’s KPIs. ? Participate in customer calls, understand their use cases, and solve their problems. ? Collaborate with software teams across different locations.

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'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 the leader in Behavioral Biometrics, a technology that leverages machine learning to analyze an online users physical and cognitive digital behavior to protect individuals online. our companys mission is to unlock the power of behavior and deliver actionable insights to create a digital world where identity, trust, and ease coexist.Today, 32 of the world's largest 100 banks and 210 total financial institutions rely on our company Connect to combat fraud, facilitate digital transformation, and grow customer relationships.. our companys Client Innovation Board, an industry-led initiative including American Express, Barclays, Citi Ventures, and National Australia Bank, helps our company to identify creative and cutting-edge ways to leverage the unique attributes of behavior for fraud prevention. With over a decade of analyzing data, more than 80 registered patents, and unparalleled experience, our company continues to innovate to solve tomorrows problems.
Main responsibilities:
Data Architecture Direction: Provide strategic direction for our data architecture, selecting the appropriate componments for various tasks. Collaborate on requirements and make final decisions on system design and implementation.
Project Management: Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Cost Optimization: Monitor and optimize cloud costs associated with data infrastructure and processes.
Efficiency and Reliability: Design and build monitoring tools to ensure the efficiency, reliability, and performance of data processes and systems.
DevOps Integration: Implement and manage DevOps practices to streamline development and operations, focusing on infrastructure automation, continuous integration/continuous deployment (CI/CD) pipelines, containerization, orchestration, and infrastructure as code. Ensure scalable, reliable, and efficient deployment processes.
Our stack: Azure, GCP, Kubernetes, ArgoCD, Jenkins, Databricks, Snowflake, Airflow, RDBMS, Spark, Kafka, Micro-Services, bash, Python, SQL.

We are looking for a hands-on Data Specialist to join our growing data group, working on the practical backbone of high-scale, financial-grade systems. Youll work closely with engineers, BI, product, and business stakeholders, expert in design, build, and optimize data pipelines and integrations in a cloud-native environment.
If you thrive on solving complex data challenges, enjoy getting deep into code, and want to make an impact on fintech infrastructure, wed love to meet you.
Your Day-to-Day:
Develop, maintain, and optimize robust data pipelines and integrations across multiple systems
Build and refine data models to support analytics and operational needs
Work hands-on with data orchestration, transformation, and cloud infrastructure (AWS/Azure)
Collaborate with engineering, BI, and business teams to translate requirements into scalable data solutions
Contribute to data governance, data quality, and monitoring initiatives
Support implementation of best practices in data management and observability