לוח משרות דרושים ראש צוות דאטה

Requirements:
2+ years leading engineers (team lead or manager) building/operating large-scale data platforms; 5+ years total in Data Infrastructure/DataOps roles.
Proven ownership of cloud-native data platforms on AWS: S3, EMR (preferably EMR on EKS), IAM, Glue/Data Catalog, Athena.
Production experience with Apache Iceberg (schema evolution, compaction, retention, metadata ops) and columnar formats (Parquet/Avro).
Hands-on depth in at least two of: Trino/Presto, Apache Spark/Structured Streaming, Apache Druid, Apache Flink.
Strong conceptual understanding of Kubernetes (EKS), including autoscaling, isolation, quotas, and observability
Strong SQL skills and extensive experience with performance tuning, with solid proficiency in Python/Java.
Solid understanding of Kafka concepts, hands-on experience is a plus
Experience running on-call for data platforms and driving measurable SLO-based improvements.
You might also have:
Experience building feature platforms (feature definitions, materialization, serving, and online/offline consistency).
Airflow (or similar) at scale; Argo experience is a plus.
Familiarity with BigQuery (and ideally BigLake/Iceberg interop) and operational DBs like Aurora MySQL.
Experience with Clickhouse / Snowflake / Databricks / Starrocks.
FinOps background (cost attribution/showback, Spot strategies).
Data quality, lineage, and cataloging practices in large orgs.
IaC (Terraform/CloudFormation).

Requirements:
8+ years of software/data engineering (strong Python preferred; JVM/Go welcome).
4+ years working with large-scale data lakes/lakehouses, including Iceberg (or similar formats). Experience with Apache Spark for heavy batch / ML pipelines is a plus.
2+ years leading engineers, while still being hands-on.
Solid SQL skills and experience with much of our stack: Trino/Presto, dbt, Iceberg, Prefect/Airflow, Kubernetes, GitHub Actions.
A builders mindset: measure, improve, document, then automate.
Clear communication in English and a collaborative attitude.

Requirements:
Requirements
5+ years of experience in data analysis, with at least 2 years in a leadership role.
Strong proficiency in SQL and experience working with analytical data warehouses (such as BigQuery and Snowflake) and BI tools (such as Looker and Tableau).
Bachelors degree in Engineering, Statistics, Computer Science, or a related field (or equivalent experience).
Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced environment.
Excellent communication skills with the ability to translate complex data into actionable business insights.
Experience in hiring, mentoring, and leading an analytics team.

Bonus if you have:
Knowledge of scripting languages (Python, R), or machine learning concepts.
Familiarity with data engineering concepts and cloud-based data platforms.

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:
At least 7 years of experience in backend or data engineering, with a minimum of 3 years in a team lead role.
Experience with development, deployment and automation on AWS - S3, SNS, lambda, batch, dynamo, RDS etc.
Expertise in advanced SQL, including writing complex, efficient queries and building optimized datasets.
Proficient in Python and Python-based data tools.
Working with micro-services on K8S
Proven track record of delivering large-scale, high-quality products
Independent, autodidact with excellent problem solving and passion to learn cutting-edge technologies
Proven ability to lead and mentor a team, manage projects, and collaborate effectively with cross-functional teams.
Outstanding interpersonal skills
Advantage:
Experience in building data stream pipelines and ETL using Big Data frameworks such as Spark and Apache Airflow
Experience with Serverless frameworks
Experience with streaming technologies such as Amazon Kinesis and Apache Kafka.

Requirements:
Hands-on Experience building cloud-scalable, real-time and high-performance Data Solutions of 3-5 years in a capacity of a team leader.
Strong Programming Skills with Python/Scala (Java in addition is a plus).
Solid engineering foundations (good coding practices, good architectural design skills).
Proven experience and in depth knowledge with one or more of the following data platforms. Certifications are desired
Big Query big advantage
Databricks
Snowflake
Proven experience with building data pipelines, preferably with Airflow, DBT, Spark and alike
Experience with ETL tools like Rivery, Fivetran, Talend or others
Solid cloud development experience in one or more cloud providers. Certifications are desired
Advanced SQL knowledge and capabilities
Experience or knowledge in AI/GenAI/ML/MLOps - advantage
Team player, positive, likes to dream big and fulfill dreams all at the same time.

Requirements:
5-10 years of experience in SAP Data & Analytics, with at least 3 years in a managerial/team lead role Must.
Proven experience managing and mentoring DATA/BI teams in large-scale, cross-organizational SAP projects.
Demonstrated ability to define and execute data and BI strategy, including architecture, governance, and innovation.
Hands-on familiarity with SAP Datasphere (Data Warehouse Cloud), SAP BW/4HANA, SAP Data Intelligence, and SAP Analytics Cloud (SAC) , BTP .
Experience integrating SAP systems (S/4HANA, ECC) with BI platforms, Data Lakes, and cloud environments.
Experience with additional modern data technologies such as Databricks, Snowflake, Azure Data Services, AWS Data Services, Google BigQuery, or similar.
Strong business acumen and ability to translate business requirements into SAP data solutions.
Excellent leadership, interpersonal, and communication skills, including experience working with global teams and presenting to senior management.
Bachelors degree in Computer Science, Software Engineering, Information Systems, or a related field.
Fluent English (spoken, written, and reading).

Requirements:
Proven Leadership: Experience in leading and managing a team, with a track record of driving results.
Exceptional Communication: Full working proficiency in English is a must. Strong presentation and client-facing skills with the ability to communicate effectively at all levels.
Data-Oriented Mindset: Experience working with datasets or transit data (GTFS is a plus). High attention to detail and strong organizational skills.
Technical Aptitude: Ability to learn and implement new technical tools quickly.
Problem-Solving: A solution-oriented mindset with the ability to manage multiple projects simultaneously in a dynamic environment.
Experience: Previous experience in a similar role, preferably within a tech or operations-focused company. Experience with tools like Microsoft Office/G Suite (especially Excel/Sheets) and Jira is required.
Desired Qualifications:
Familiarity with transit networks in major cities.
Experience in customer-facing roles, such as customer support or success management.
A passion for public transit and urban mobility.

Requirements:
A minimum of 4 years of experience as a BI system analyst / BI Developer / Analytics engineer, demonstrating a deep understanding of data platform design, and how business definitions turn to metrics, AI, and semantic layer concepts.
Proven experience in applying data solutions to solve business problems and drive business improvement.
Advanced proficiency in analytical tools and programming languages (e.g., SQL-Critical, Python - nice to have) and familiarity with data visualization tools (e.g., Tableau, Power BI).
Expertise in embedding a data-centric culture, enhancing data literacy and decision-making across the organization
Effective collaboration and project management capabilities, with experience leading cross-functional projects.

Requirements:
* Minimum of 2 years of managerial experience
* At least 4 years of hands-on experience in marketing analytics
* Knowledge of the entire marketing ecosystem, paid and organic
* Familiarity with measurement methodologies and frameworks used to evaluate marketing effectiveness
* Strong analytical skills and proficiency with data tools and software
* Excellent leadership, communication, and teamwork skills
At our company, were not about checklists. If you dont meet 100% of the requirements for this role but still feel passionate about the position and think you have the right skills and qualifications to excel at it, we want to hear from you.