דרושים » הנדסה » A global FinTech company is looking for a Data Engineer!

Requirements:
5+ years of hands-on experience as a Data Engineer, building data systems from scratch in dynamic environments.
Bachelors degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
Strong proficiency in Python and advanced SQL, with solid experience in data modeling.
Proven experience designing and building scalable data pipelines (batch and real-time), including streaming technologies such as Kafka.
Strong experience working with AWS, including services such as S3, Athena and DynamoDB.
Experience working with big data processing frameworks such as Spark, and columnar data formats (e.g., Parquet).
Hands-on experience with workflow orchestration tools such as Airflow.
Strong ownership and execution mindset, with excellent problem-solving skills and high attention to detail, and the ability to collaborate effectively and deliver in ambiguous, fast-paced environments.
Fluent in English.
Nice to have:

Experience with data platform technologies such as Databricks, Snowflake.
Experience building data platforms using modern lakehouse technologies (e.g., Iceberg).

Requirements:
Required Skills and Experience
Bachelors degree or higher in Computer Science, Software Engineering, EE, Information Systems, or a related field
Minimum 8+ years of experience as a Dataflow and DevOps development, Backend Engineer, Data Engineer, or similar role
Strong experience with Python
Strong SQL skills, including query optimization, indexing, stored procedures, and performance tuning
Experience with ETL/ELT processes, data pipelines, and integration between systems
Strong experience with automation scripting language (ex: Groovy), data processing, and tooling
Experience with Docker, Kubernetes, Jenkins and CI/CD frameworks
Familiar with developing in Linux and Windows environments
Experience with backup, restore, migration, monitoring, and database maintenance processes
Understanding of data security, permissions, access control, and data integrity practices
Experience with Git, Jira, and Agile development workflows
High English skills: listening, speaking, and reading (C1-2)
Nice to have:
Past experience with CloudBees, Antifactory, and integrating them into a secure system
Strong experience with relational databases such as PostgreSQL and Pgvector, MySQL, and NoSQL
Experience with cloud database services such as AWS RDS, Azure SQL, Google Cloud SQL, or similar
Experience with database schema design, data modelling, and database normalization
Experience with AI agents and AI automation
Familiarity with database replication, clustering, high availability, and disaster recovery
Experience with BI/reporting tools or data visualization platforms
Experience with backup solutions and backup strategies
Experience working in an R&D, semiconductor, embedded systems, or hardware/software engineering environment
Experience and background in MAL, datasets, and MAL Python libraries.
Experience in JAVA.

Requirements:
5+ years in data engineering, with real production experience at scale (terabytes+, billions of rows)
Deep SQL and strong distributed-processing experience (Spark or equivalent)
Strong Python and/or Go
Hands-on experience with cloud data warehouses (BigQuery, Snowflake, Redshift) and orchestration tooling
AI-first mindset - you actively work with AI coding tools (Claude Code, Cursor, Copilot) and LLM-based agents as part of your day-to-day, and look for opportunities to automate and accelerate engineering work with them
Experience building or supporting AI/LLM-driven data products - pipelines that feed models, agents, or ML systems
Product mindset: you care why the data is being used, not just that the job finished green
Nice to have: streaming architectures, cost/FinOps ownership, multi-region or multi-cloud systems, e-commerce or pricing domain experience, MCP servers or agentic tooling.

Requirements:
5+ years of experience with advanced data modeling techniques and concepts (e.g., Facts, Dimensions, Partitions).
5+ years of experience designing and implementing end-to-end data ingestion and ETL processes within Data Lakehouse architectures.
5+ years of hands-on experience programming in SQL and Python, PySpark, Java, or Scala.
Demonstrated experience leading technical projects, driving stakeholder alignment, and navigating cross-functional dynamics.
Proven experience working within cloud environments (AWS or GCP), with a strong requirement for AWS.
Deep understanding of the modern data landscape and open-source tools (e.g., Iceberg, DBT, Airflow).
Proven capability in using and orchestrating Gen-AI workflows based on CloudCode and Cursor.
Preferred Qualifications
Deep expertise in the AWS ecosystem, including Glue, Athena, SageMaker, and EMR.
Advanced experience with Data Warehouse technologies, especially Apache Iceberg or BigQuery.
Leadership or mentorship experience within a data engineering or analytics unit.
Background or domain knowledge in cybersecurity is a strong advantage.

Requirements:
Required Qualifications
5+ years of experience with advanced data modeling techniques and concepts (e.g., Facts, Dimensions, Partitions).
5+ years of experience designing and implementing end-to-end data ingestion and ETL processes within Data Lakehouse architectures.
5+ years of hands-on experience programming in SQL and Python, PySpark, Java, or Scala.
Demonstrated experience leading technical projects, driving stakeholder alignment, and navigating cross-functional dynamics.
Proven experience working within cloud environments (AWS or GCP), with a strong requirement for AWS.
Deep understanding of the modern data landscape and open-source tools (e.g., Iceberg, DBT, Airflow).
Proven capability in using and orchestrating Gen-AI workflows based on CloudCode and Cursor.
Preferred Qualifications:
Deep expertise in the AWS ecosystem, including Glue, Athena, SageMaker, and EMR.
Advanced experience with Data Warehouse technologies, especially Apache Iceberg or BigQuery.
Leadership or mentorship experience within a data engineering or analytics unit.
Background or domain knowledge in cybersecurity is a strong advantage.
Our

Requirements:
Required Qualifications:
5+ years of experience with advanced data modeling techniques and concepts (e.g., Facts, Dimensions, Partitions).
5+ years of experience designing and implementing end-to-end data ingestion and ETL processes within Data Lakehouse architectures.
5+ years of hands-on experience programming in SQL and Python, PySpark, Java, or Scala.
Demonstrated experience leading technical projects, driving stakeholder alignment, and navigating cross-functional dynamics.
Proven experience working within cloud environments (AWS or GCP), with a strong requirement for AWS.
Deep understanding of the modern data landscape and open-source tools (e.g., Iceberg, DBT, Airflow).
Proven capability in using and orchestrating Gen-AI workflows based on CloudCode and Cursor.
Preferred Qualifications:
Deep expertise in the AWS ecosystem, including Glue, Athena, SageMaker, and EMR.
Advanced experience with Data Warehouse technologies, especially Apache Iceberg or BigQuery.
Leadership or mentorship experience within a data engineering or analytics unit.
Background or domain knowledge in cybersecurity is a strong advantage.

Requirements:
5+ years of relevant experience as Data Engineer - a must.
Experience with Python based data pipelines/ETLs and other ETL\ELT tools (such as Glue, Rivery, Data Factory, DBT).
High Proficiency in SQL - a must.
Experience designing and developing DWHs in the cloud - Redshift\Snowflake\BigQuery is a must.
Experience with BI & visualizations tools like Tableau\Quicksight\Power BI\Looker.
Knowledge and experience with AI\ML (working with tools like SageMaker\ Bedrock\ Q\ BigQuery ML\ Vertex AI\ Gemini) - big advantage.
Strong analytical and problem-solving skills with attention to details.
High self-learning skills
Fluent English.

Requirements:
5+ years in data engineering.
Expertise in Apache Spark and Spark Structured Streaming.
Hands-on experience with Apache Iceberg or similar data lakes.
Proficiency in Scala, Java, or Python.
Knowledge of big data technologies (Hadoop, Hive, Presto).
Experience with cloud platforms (AWS, Azure, GCP) and SQL.
Strong problem-solving, communication, and collaboration skills.

Requirements:
What we need to see:

B.Sc/M.Sc/Phd degree in Computer Science, Computer Engineering, or Electrical Engineering.

2+ years of experience as SW Architect/System Architect.

2+ years of experience as SW developer.

Deep knowledge and experience with C, Python.

Hands on Linux development, Docker and Containers based technologies.

Experience with cloud and Data Center networking.

Wide knowledge and understanding of networking protocols and common network topologies.

Strong design, coding, analytical, debugging and problem-solving skills.

Ability to work concurrently with multiple groups locally and abroad in the organization.

Excellent communication, documentation and presentation skills


Ways to stand out from a crowd:

Development experience with networking/security devices - NICs/DPUs/Switches/Routers /Firewalls etc.

Good understanding of OSs and drivers.

Experience with DPDK, OVS, OVN.

Experience with Kubernetes components & subsystems, CRDs, Operators, system plugins and CNI plugin development (Calico, Flannel).

Experience with OpenStack/OpenShift and/or Cloud APIs.