דרושים » דאטה » Data Engineer For Data Group

Were looking for a Data Engineer for the Insight Team to join Lushas Data Group and a new team responsible for developing innovative features based on multiple layers of data. These features will power recommendation systems, insights, and more. This role involves close collaboration with the core teams within the Data Group, working on diverse data pipelines that tackle challenges related to scale and algorithmic optimization, all aimed at enhancing the data experience for Lushas customers.
What will you be responsible for?
Develop and implement robust, scalable data pipelines and integration solutions within Lushas Databricks-based environment.
Develop models and implement algorithms, with a strong emphasis on delivering high-quality results.
Leverage technologies like Spark, Kafka, and Airflow to tackle complex data challenges and enhance business operations.
Design innovative data solutions that support millions of data points, ensuring high performance and reliability.

We're seeking an outstanding and passionate Data Platform Engineer to join our growing R&D team.
You will work in an energetic startup environment following Agile concepts and methodologies. Joining the company at this unique and exciting stage in our growth journey creates an exceptional opportunity to take part in shaping Finaloop's data infrastructure at the forefront of Fintech and AI.
What you'll do:
Design, build, and maintain scalable data pipelines and ETL processes for our financial data platform.
Develop and optimize data infrastructure to support real-time analytics and reporting.
Implement data governance, security, and privacy controls to ensure data quality and compliance.
Create and maintain documentation for data platforms and processes
Collaborate with data scientists and analysts to deliver actionable insights to our customers.
Troubleshoot and resolve data infrastructure issues efficiently
Monitor system performance and implement optimizations
Stay current with emerging technologies and implement innovative solutions
Tech stack: AWS Serverless, Python, Airflow, Airbyte, Temporal, PostgreSQL, Snowflake, Kubernetes, Terraform, Docker.

We are making the future of Mobility come to life starting today.
At our company we support the worlds largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization.
At the heart of our platform lies the data infrastructure, driving advanced machine learning models and optimization algorithms. As the owner of data pipelines, you'll tackle diverse challenges spanning optimization, prediction, modeling, inference, transportation, and mapping.
As a Senior Data Engineer, you will play a key role in owning and scaling the backend data infrastructure that powers our platformsupporting real-time optimization, advanced analytics, and machine learning applications.
What You'll Do
Design, implement, and maintain robust, scalable data pipelines for batch and real-time processing using Spark, and other modern tools.
Own the backend data infrastructure, including ingestion, transformation, validation, and orchestration of large-scale datasets.
Leverage Google Cloud Platform (GCP) services to architect and operate scalable, secure, and cost-effective data solutions across the pipeline lifecycle.
Develop and optimize ETL/ELT workflows across multiple environments to support internal applications, analytics, and machine learning workflows.
Build and maintain data marts and data models with a focus on performance, data quality, and long-term maintainability.
Collaborate with cross-functional teams including development teams, product managers, and external stakeholders to understand and translate data requirements into scalable solutions.
Help drive architectural decisions around distributed data processing, pipeline reliability, and scalability.

We are looking for a Data Backend Engineer.
What will you be responsible for?
Design and build distributed data systems that are the backbone of our product innovation.
Architect and implement high-throughput data pipelines capable of handling billions of records with speed and reliability.
Develop custom algorithms for deduplication, data merging, and real-time data updates.
Optimize storage, indexing, and retrieval strategies to manage massive datasets efficiently.
Solve deep engineering challenges in distributed computing environments like Spark, EMR, and Databricks.
Build fault-tolerant, highly available data infrastructure with integrated monitoring and observability.
Partner closely with ML engineers, backend developers, and product managers to turn business needs into scalable, production-grade features.

At our company, were reinventing DevOps and MLOps to help the worlds greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if youre willing to do more, your career can take off. And since software plays a central role in everyones lives, youll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust our company to manage, accelerate, and secure their software delivery from code to production - a concept we call liquid software. Wouldn't it be amazing if you could join us in our journey?
About the Team
We are seeking a highly skilled Senior Data Engineer to join our company's ML Data Group and help drive the development and optimization of our cutting-edge data infrastructure. As a key member of the company's ML Platform team, you will play an instrumental role in building and evolving our feature store data pipeline, enabling machine learning teams to efficiently access and work with high-quality, real-time data at scale.
In this dynamic, fast-paced environment, you will collaborate with other data professionals to create robust, scalable data solutions. You will be responsible for architecting, designing, and implementing data pipelines that ensure reliable data ingestion, transformation, and storage, ultimately supporting the production of high-performance ML models.
We are looking for data-driven problem-solvers who thrive in ambiguous, fast-moving environments and are passionate about building data systems that empower teams to innovate and scale. We value independent thinkers with a strong sense of ownership, who can take challenges from concept to production while continuously improving our data infrastructure.
As a Data Engineer at our company's ML you will...
Design and implement large-scale batch & streaming data pipelines infrastructure
Build and optimize data workflows for maximum reliability and performance
Develop solutions for real-time data processing and analytics
Implement data consistency checks and quality assurance processes
Design and maintain state management systems for distributed data processing
Take a crucial role in building the group's engineering culture, tools, and methodologies
Define abstractions, methodologies, and coding standards for the entire Data Engineering pipeline.

We seek a Director of Data to join us and lead our data group.
As our Director of Data, you will be a key member of our R&D leadership team. You will be responsible for developing and executing a data strategy that aligns with our business goals, overseeing data management, analytics, and validation, and ensuring data integrity at every stage of product development and production.
A day in the life and how youll make an impact:
Define and execute a strategic data roadmap aligned with business objectives, fostering a data-driven culture and leading a high-performing team of data engineers, scientists, and analysts.
Establish robust data validation frameworks, ensuring product integrity and accuracy through all stages, from data acquisition to end-user delivery.
Build and optimize scalable data infrastructure and pipelines to support our data needs and ensure data security, compliance, and accessibility.
Collaborate with product and engineering teams to create and launch data-driven products, ensuring they are built on reliable data and designed to meet customer needs.
Guide the team in generating actionable insights to drive business decisions and product innovation in areas such as personalization, marketing, and customer success.
Implement data governance policies and maintain compliance with industry regulations and best practices.

We are looking for a Data Engineering Tech Lead.
What will you be responsible for?
Lead the design and development of scalable, high-performance data workflows, including both batch pipelines and real-time data products.
Define, implement, and enforce engineering best practices related to code quality, testing, CI/CD pipelines, observability, and documentation.
Mentor, support, and grow a team of data engineers, fostering a collaborative and high-performance engineering culture.
Identify opportunities to create new data assets and features that expand product capabilities and value proposition.
Drive architectural decision-making in areas of data modeling, storage solutions, and compute resources within cloud environments such as Databricks and Snowflake.
Collaborate closely with cross-functional stakeholdersincluding Product, DevOps, and R&Dto ensure effective delivery and platform stability.
Promote and champion a data-driven mindset across the organization, balancing technical rigor with business context and strategic goals.

Were looking for a Data Analyst for the Data Group to work alongside top-tier data professionals, data scientists, and data engineering teams. You will be an integral part of the group ecosystem, providing insights that impact hundreds of thousands of users by leveraging advanced data systems.
What will you be responsible for?
Deeply understand the architecture of Data Group, driving the development of advanced analyses and data models, while collaborating with cross-functional teams to design and implement enrichment logic within our data ecosystem.
Develop tools, build dashboards, and establish methodologies to analyze user behavior and enhance the data experience for users.
Leverage Data Lake to its fullest potential, utilizing cutting-edge data exploration and visualization tools to extract insights and drive data-driven decision-making.

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.

Required Senior Data Engineer
The opportunity
Join our dynamic Data & ML Engineering team in iAds and play a pivotal role in driving data solutions that empower data science, finance, analytics, and R&D teams. As an Experienced Data Engineer, you'll work with cutting-edge technologies to design scalable pipelines, ensure data quality, and process billions of data points into actionable insights.
Success Indicators
In the short term, success means delivering reliable, high-performance data pipelines and ensuring data quality across the product. Long-term, you'll be instrumental in optimizing workflows, enabling self-serve analytics platforms, and supporting strategic decisions through impactful data solutions.
Impact
Your work will directly fuel business decisions, improve data accessibility and reliability, and contribute to the team's ability to handle massive-scale data challenges. You'll help shape the future of data engineering within a global, fast-paced environment.
Benefits and Opportunities
You'll collaborate with talented, passionate teammates, work on exciting projects with cutting-edge technologies, and have opportunities for professional growth. Competitive compensation, comprehensive benefits, and an inclusive culture make this role a chance to thrive and make a global impact.
What you'll be doing
Designing and developing scalable data pipelines and ETL processes to process massive amounts of structured and unstructured data.
Collaborating with cross-functional teams (data science, finance, analytics, and R&D) to deliver actionable data solutions tailored to their needs.
Building and maintaining tools and frameworks to monitor and improve data quality across the product.
Providing tools and insights that empower product teams with real-time analytics and data-driven decision-making capabilities.
Optimizing data workflows and architectures for performance, scalability, and cost efficiency using cutting-edge technologies like Apache Spark and Flink.