דרושים » תוכנה » Senior Data Infrastructure Engineer

Requirements:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions
Strong knowledge of databases, including SQL (schema design, query optimization) and NoSQL, with a solid understanding of their use cases
Ability to work in an office environment a minimum of 3 days a week
Enthusiasm about learning and adapting to the exciting world of AI a commitment to exploring this field is a fundamental part of our culture.

Requirements:
At least 10 years of experience in a data engineering role, including 2+ years as a data & AI 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
Excellent proficiency in SQL, and in either Python or JavaScript.
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.
Willingness 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.

Requirements:
5+ years of hands-on experience as a Data Engineer, building and operating production-grade data systems.
3+ years of experience with Spark, SQL, Python, and orchestration tools like Airflow (or similar).
Degree in Computer Science, Engineering, or a related quantitative field.
Proven track record in designing and implementing high-scale ETL pipelines and real-time or batch data workflows.
Deep understanding of data lakehouse and warehouse architectures, dimensional modeling, and performance optimization.
Strong analytical thinking, debugging, and problem-solving skills in complex environments.
Familiarity with infrastructure as code, CI/CD pipelines, and building data-oriented microservices or APIs.
Enthusiasm for AI-driven developer tools such as Cursor.AI or GitHub Copilot.
Bonus points:
Hands-on experience with our stack: Databricks, Delta Lake, Kafka, Docker, Airflow, Terraform, and AWS.
Experience in building self-serve data platforms and improving developer experience across the organization.

Requirements:
BS or MS degree in Computer Science or a related technical field.
3-4 years of Python / Java development experience.
3-4 years of experience as a Data Engineer or in a similar role (BI developer).
3-4 years of direct experience with SQL (No-SQL is a plus), data modeling, data warehousing, and building ELT/ETL pipelines - MUST
Experience working with cloud environments (AWS preferred) and big data technologies (EMR,EC2, S3 ) - DBT is an advantage.
Experience working with Airflow - big advantage
Experience working with Kubernetes advantage
Experience working with at least in one of the big data environments: Snowflake, Vertica, Hadoop (Impala/Hive), Redshift etc MUST
Experience working with Spark advantage
Exceptional troubleshooting and problem-solving abilities.
Excellent verbal/written communication & data presentation skills, including experience communicating to both business and technical teams.

Requirements:
* B.Sc. in Computer Science, data Engineering, or a related field.
* 3+ years of hands-on experience in large-scale data infrastructures.
* Strong Python programming, with expertise in PySpark and Pandas.
* Deep knowledge of SQL and NoSQL databases, including performance optimization.
* Experience with ElasticSearch and AWS cloud services.
* Solid understanding of DevOps practices, Big Data tools, Git, and Jenkins.
* Familiarity with microservices and event-driven design.
* Strong problem-solving skills and a proactive, independent mindset. Advantages
* Experience with LangChain, ClickHouse, DynamoDB, Redis, and Apache Kafka.
* Knowledge of Metabase for data visualization.
* Experience with RESTful APIs and Node.js. Talent We Are Looking For Independent & Self-Driven Comfortable building from the ground up. Growth-Oriented Eager to develop professionally and take on leadership roles. Innovative Passionate about solving complex data challenges. Collaborative Strong communicator who works well with cross-functional teams. Adaptable Thrives in a fast-paced, dynamic environment with a can-do attitude. About the Company: Appdome's mission is to protect every mobile app worldwide and its users. We provide mobile brands with the only patented, centralized, data -driven Mobile Cyber Defense Automation platform. Our platform delivers rapid no-code, no-SDK mobile app security, anti-fraud, anti-malware, anti-cheat, anti-bot implementations, configuration as code ease, Threat-Events threat-aware UI / UX control, ThreatScope Mobile XDR, and Certified Secure DevSecOps Certification in one integrated system. With Appdome, mobile Developers, cyber and fraud teams can accelerate delivery, guarantee compliance, and leverage automation to build, TEST, release, and monitor the full range of cyber, anti-fraud, and other defenses needed in mobile apps from within mobile DevOps and CI/CD pipelines. Leading financial, healthcare, m-commerce, consumer, and B2B brands use Appdome to upgrade mobile DevSecOps and protect Android & IOS apps, mobile customers, and businesses globally. Today, Appdome's customers use our platform to secure over 50,000+ mobile apps, with protection for over 1 billion mobile end users projected.
Appdome is an Equal Opportunity Employer. We are committed to diversity, equity, and inclusion in our workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law. All qualified applicants will receive consideration for employment without regard to any of these characteristics.

Requirements:
BSc. Computer Science, Engineering or similar.
Minimum of 4 years of professional experience in data engineering
Minimum of 4 years of professional experience in backend or software development
Independent, responsible, ready to face challenges head-on
Passionate about data engineering and constantly expanding your knowledge
Excellent communication and strong analytical and problem-solving skills
Proficient in Python
Experience with Data streaming, Kafka, Airflow, cloud platforms (preferably AWS), k8s, terraform or equivalents.
Have a solid background working with data warehousing technologies, such as Snowflake, Databricks, Redshift, BigQuery, etc.

Requirements:
To thrive in this role, youll need:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills in Java & Python
Experience with TensorFlow a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
3+ years of experience in data engineering, building and optimizing scalable data pipelines.
5+ years of experience as a software developer, preferably in Python.
Algorithmic experience, including developing and optimizing machine learning models and implementing advanced data algorithms.
Experience working with cloud ecosystems, preferably AWS (S3, Glue, EMR, Redshift, Athena) or comparable cloud environments (Azure/GCP).
Expertise in extracting, ingesting, and transforming large datasets efficiently.
Deep knowledge of big data platforms, such as Spark, Databricks, Elasticsearch, and Kafka for real-time data streaming.
(Nice-to-have) Hands-on experience working with Vector Databases and embedding techniques, with a focus on search, recommendations, and personalization.
AI-savvy: comfortable working with AI tools and staying ahead of emerging trends.

Requirements:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills in Java & Python
Experience with TensorFlow a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
5+ years of proven experience with designing, implementing, and maintaining large-scale backend production systems
Experience building and maintaining data-intensive applications
Experience with data processing technologies, e.g. Spark, Flink, EMR, Iceberg
Experience with data warehousing frameworks, e.g. Snowflake, Hive, Glue, Databricks Unity Catalog
Experience working in Python
Experience with AWS or other public clouds
Professional proficiency in English