דרושים » ניהול ביניים » Data Team Lead

Requirements:
1. Technical Expertise
Cloud Data Platforms: Expertise in Google Cloud Platform (GCP)
services, especially in data-related services like BigQuery, Cloud SQL,
Dataproc, Pub/Sub, and Dataflow.
Data Engineering: Strong knowledge of data pipelines, ETL/ELT
processes, and data integration using GCP tools.
Database Management: Experience with both relational and
non-relational databases, including MySQL, PostgreSQL, and NoSQL
solutions like Firestore or Bigtable.
Programming Skills: Proficiency in Python, SQL, and possibly other
languages like Java or Scala, with a focus on data manipulation and
processing.
APIs and Integrations: Experience working with Google APIs and
third-party APIs for data extraction and integration.
Machine Learning: Familiarity with Google Cloud AI tools, such as
Vertex AI, and how to integrate machine learning workflows into the data
architecture.
Data Governance: Knowledge of data security, privacy, governance, and
regulatory requirements (GDPR, HIPAA, etc.).
2. Leadership and Management
Team Management: Ability to lead a team of data engineers, analysts,
and architects, providing guidance, mentorship, and performance
management.
Project Management: Strong skills in managing data projects, ensuring
timely delivery while meeting client requirements.
Collaboration: Experience working cross-functionally with stakeholders
such as solution architects, developers, and business teams to translate
business needs into data solutions.
Resource Allocation: Efficiently managing cloud resources to optimize
cost and performance.
3. Client-Facing Skills
Consulting: Experience in providing consulting services to clients,
including understanding their data needs, providing solutions, and
guiding them through the data modernization process.
Pre-sales Support: Supporting sales teams in scoping out client
projects, preparing presentations, and explaining technical aspects of
data solutions during pre-sales.
Client Relationship Management: Building and maintaining strong
relationships with clients to ensure satisfaction and long-term
partnership.
4. Certifications and Education
● Google Cloud Certifications:
● Professional Data Engineer (preferred)
● Professional Cloud Architect (preferred)
● Other Certifications: Optional certifications in data engineering or
machine learning from organizations like Cloudera, AWS, or Microsoft
Azure can be advantageous.
● Educational Background: Bachelors or Masters degree in Computer
Science, Data Science, Engineering, or a related field.
5. Soft Skills
● Problem-Solving: Ability to troubleshoot data-related issues and
implement scalable solutions.
● Adaptability: Ability to keep up with the rapidly changing cloud and data
landscape.
● Communication: Excellent verbal and written communication skills to
explain complex data systems to non-technical stakeholders.

Requirements:
Bachelors degree in computer science, Software Engineering, or a related field.
3+ years of experience as a data engineering team leader in a product-based company.
5+ years of hands-on in SQL and Python / Pyspark (or Java / Scala), data modeling techniques and concepts - such as Facts, Dimension, Partitions, etc.
Experience in designing and implementing data ingestion, ETL processes and 3rd party tools, preferably with experience in Data Lakehouse and Data Warehouse architecture
Proven experience with CI/CD processes and agile development methodologies.
Strong interpersonal and communication skills.
Demonstrated ability to manage and develop a team with varying levels of experience.
Skilled in identifying risks, tracking progress, and resolving technical challenges proactively.
Self-motivated and goal-oriented with a high work ethic.
Ability to balance long-term architectural vision with fast-paced delivery, in early-stage development or startup environment.

Requirements:
B.Sc. in Computer Science, Software Engineering, or a related field (or equivalent experience).
10+ years of experience in software development, with a focus on software system architecture.
4+ years of experience leading engineering teams and managing end-to-end project lifecycles.
Strong background in building large-scale, high-performance financial or transactional systems.
Experience with data pipelines, big data infrastructure, microservices architecture, and message bus.
Hands-on experience with Java and Python, and modern cloud technologies.
Ability to collaborate and communicate effectively across engineering, finance, risk, and product stakeholders.
Adaptability to thrive in a fast-paced, dynamic environment.
Solution-oriented mindset with a proactive approach to problem-solving.
Proficiency in written and spoken English.
Advantages:
Working knowledge of Kotlin.
Prior experience in fintech or payment systems.
Familiarity with loan and card performance data products and internal/external reporting use cases.

Requirements:
B.Sc in computer science or equivalent.
Experience managing a team (preferably 3+ years) and leading projects hands-on from start to finish (preferably 8+ years, focusing on system architecture).
Proficiency in modern system architecture with large-scale and high performance.
Impact driven - use data to make sure every task moves the needle and utilize your resources to maximize the team's impact.
Team player, with strong communication skills and someone who thrives working in a fast-paced environment.
Creative, solution-oriented, and able to maintain a can do attitude, with the ability to work efficiently under pressure and uncertainty. Adapt quickly to changing business needs.
Passion for data.
Experience with microservices architecture
Fluent in English.
Preferred Experience:
Experience with software development in Python.
Experience with cloud technology.
Experience in managing data specialists (AI/ML engineers, analysts).

Requirements:
8+ years of experience in software development, with at least 3 years in a leadership role managing multiple teams.
Proven experience in building and maintaining large-scale data pipelines and distributed systems
Strong hands-on experience with AWS services
Deep understanding of data models, ETL processes, and stream processing (e.g., Kafka, Kinesis)
Proficiency in Python and Java
Experience working in an Agile environment and high-pace delivery
Bachelors or Masters degree in Computer Science, Engineering, or a related field
A team player with excellent communication and leadership skills
Fluent English (written & spoken).

Requirements:
6+ years of industry experience in AI/ML or Data Science, with at least 1-year leading teams and managing direct reports.
Masters degree or PhD in a technical field (e.g., Computer Science, Machine Learning, Statistics, Engineering).
Solid proficiency in Python and machine learning libraries/frameworks such as scikit-learn, PyTorch, TensorFlow, or Hugging Face.
Strong familiarity with natural language processing (NLP), including LLMs and transformer-based architectures, and their applications to real-world use cases.
Strong technical communication skills and the ability to collaborate across cross-functional teams.
Strategic mindset with the ability to connect AI research to business value and product opportunities.
Additional Information
Familiarity with cybersecurity, identity security, or risk mitigation use cases.
Experience with cloud-based ML infrastructure (e.g., AWS SageMaker, GCP Vertex AI) and big data tools (e.g., Spark, Airflow).
Hands-on knowledge of MLOps tooling for CI/CD, monitoring, and versioning of ML assets.
Publications, patents, or open-source contributions in AI/ML.

Requirements:
What makes you a great fit 5+ years of professional.NET ( C #) backend experience. Strong foundation in object-oriented design (OOD), Design Patterns, and Software Engineering best practices.Practical experience with Event Driven Architecture (EDA) and Business Process Management (BPM). Hands-on with messaging/queueing systems like Kafka, RabbitMQ, Azure EventHub, AWS SNS (or equivalents). Familiarity with rules engines (advantage). Solid experience in Cloud Native development (Azure/AWS/GCP). Practical experience using AI in development workflows, including GitHub Co-Pilot, AI Agents, and MCP Servers. Practical experience with microservices and domain-driven design. Hands-on with EF Core and data modeling. Comfortable across SQL server, PostgreSQL, and Redis. You write automated unit and integration tests by default. Experience with Azure DevOps, Kubernetes, Docker, and modern CI/CD. Solid grasp of security and observability (HTTPS, authN/authZ, structured loggingSerilog). Thrive in Agile teams, strong communicator and mentor. Bonus: background in fintech/insurance. Practical experience using AI in development workflows, including GitHub Co-Pilot, AI Agents, and MCP Servers. Bonus: Experience with PowerApps, DataVerse, MS Dynamics CRM 365; exposure to NoSQL/Object DBs (e.g. MongoDB); ORM frameworks. Team player with strong collaboration skills. What we offer A chance to shape the Future Ready of enterprise systems used globally. A supportive, collaborative culture where innovation is encouraged. A vibrant, high-energy working environment with a

Requirements:
2+ years of leadership experience, guiding engineering teams and making architectural decisions
8+ years of software engineering experience, with a strong focus on scalable architecture and system design
Proficiency in modern system architecture with large-scale and high performance.
Impact driven - use data to make sure every task moves the needle and utilize your resources to maximize the team's impact.
Team player with strong communication skills and someone who thrives working in a fast-paced environment.
Creative, solution-oriented, and able to maintain a can do attitude, with the ability to work efficiently under pressure and uncertainty. Adapt quickly to changing business needs.
Familiarity with microservices architecture and distributed systems.
B.Sc in computer science or equivalent.
Fluent in English.
Preferred Experience:
Experience with software development in Kotlin or Java.
Experience with Frontend technologies.
Experience with mobile technologies.
Leading a multidisciplinary team.
Familiarity with microservices architecture and distributed systems.
Solid understanding of AWS or similar cloud platforms.
Expertise in the Spring Framework.
Proficient in both relational (e.g., MySQL) and non-relational databases (e.g., MongoDB).
Familiarity with message queue technologies such as Kafka, SQS, RabbitMQ, or similar.

Requirements:
Qualifications
6+ years of backend engineering experience, including at least 2+ years in a technical leadership or management role.
Strong expertise in distributed systems, high-scale architectures, and backend frameworks (e.g., Java, .NET, Go, Node.js adjust to our companys tech stack).
Solid understanding of databases, API design, and system integrations.
Proven ability to lead engineering teams, mentor individuals, and foster collaboration.
Excellent communication and problem-solving skills.
Experience in fintech, mobility, or transactional systems is a strong advantage.