Lsports Inc
Software Architect · Full-time · Senior R&D Tel Aviv , IL
Lsports Inc, Chicago, Illinois, United States
LSports is a leading global provider of sports data, dedicated to revolutionizing the industry through innovative solutions. We excel in sports data collection and analysis, advanced data management, and cutting-edge services like AI-based sports tips and high-quality sports visualization. As the sports data industry continues to grow, LSports remains at the forefront, delivering real-time solutions.
If you share our love of sports and tech, and have the passion and will to better the sports-tech and data industries, join the team. We are looking for a highly motivated
Software Architect . Responsibilities Define and lead the architecture of complex software systems and platforms, from design to deployment. Collaborate with cross-functional teams (Data, ML, CV, DevOps) to align architecture with product and business goals. Design and oversee the development of high-throughput, low-latency services and data pipelines. Guide the implementation of best practices in software engineering, including system design, scalability, reliability, testing, and monitoring. Evaluate and adopt technologies (e.g., Apache Iceberg, event-driven architectures, observability platforms) to improve system performance and development velocity. Mentor engineers and contribute to architectural knowledge sharing across the company. Requirements
At least 10 years of experience in a data engineering role, including 2+ years as a Software Architect with ownership over company-wide architecture decisions. Proven experience designing and implementing large-scale, Big Data infrastructure from scratch in a cloud-native environment (GCP preferred). Excellent proficiency in data modeling, including conceptual, logical, and physical modeling for both analytical and real-time use cases. Strong hands-on experience with: Data lake and/or warehouse technologies, with Apache Iceberg experience required (e.g., Iceberg, Delta Lake, BigQuery, ClickHouse). ETL/ELT frameworks and orchestrators (e.g., Airflow, dbt, Dagster). Real-time streaming technologies (e.g., Kafka, Pub/Sub). Data observability and quality monitoring solutions. Experience designing efficient data extraction and ingestion processes from multiple sources and handling large-scale, high-volume datasets. Demonstrated ability to build and maintain infrastructure optimized for performance, uptime, and cost, with awareness of AI/ML infrastructure requirements. Experience working with ML pipelines and AI-enabled data workflows, including support for Generative AI initiatives (e.g., content generation, vector search, model training pipelines) — or strong motivation to learn and lead in this space. Excellent communication skills in English, with the ability to clearly document and explain architectural decisions to technical and non-technical audiences. Fast learner with strong multitasking abilities; capable of managing several cross-functional initiatives simultaneously. Willing to work on-site in Ashkelon once a week. Advantage: Experience leading POCs and tool selection processes. Familiarity with Databricks, LLM pipelines, or vector databases is a strong plus. Plug your product into the best sports data feeds in the world.
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Software Architect . Responsibilities Define and lead the architecture of complex software systems and platforms, from design to deployment. Collaborate with cross-functional teams (Data, ML, CV, DevOps) to align architecture with product and business goals. Design and oversee the development of high-throughput, low-latency services and data pipelines. Guide the implementation of best practices in software engineering, including system design, scalability, reliability, testing, and monitoring. Evaluate and adopt technologies (e.g., Apache Iceberg, event-driven architectures, observability platforms) to improve system performance and development velocity. Mentor engineers and contribute to architectural knowledge sharing across the company. Requirements
At least 10 years of experience in a data engineering role, including 2+ years as a Software Architect with ownership over company-wide architecture decisions. Proven experience designing and implementing large-scale, Big Data infrastructure from scratch in a cloud-native environment (GCP preferred). Excellent proficiency in data modeling, including conceptual, logical, and physical modeling for both analytical and real-time use cases. Strong hands-on experience with: Data lake and/or warehouse technologies, with Apache Iceberg experience required (e.g., Iceberg, Delta Lake, BigQuery, ClickHouse). ETL/ELT frameworks and orchestrators (e.g., Airflow, dbt, Dagster). Real-time streaming technologies (e.g., Kafka, Pub/Sub). Data observability and quality monitoring solutions. Experience designing efficient data extraction and ingestion processes from multiple sources and handling large-scale, high-volume datasets. Demonstrated ability to build and maintain infrastructure optimized for performance, uptime, and cost, with awareness of AI/ML infrastructure requirements. Experience working with ML pipelines and AI-enabled data workflows, including support for Generative AI initiatives (e.g., content generation, vector search, model training pipelines) — or strong motivation to learn and lead in this space. Excellent communication skills in English, with the ability to clearly document and explain architectural decisions to technical and non-technical audiences. Fast learner with strong multitasking abilities; capable of managing several cross-functional initiatives simultaneously. Willing to work on-site in Ashkelon once a week. Advantage: Experience leading POCs and tool selection processes. Familiarity with Databricks, LLM pipelines, or vector databases is a strong plus. Plug your product into the best sports data feeds in the world.
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