לוח משרות דרושים הייטק דאטה

Requirements:
* Bachelors degree in Statistics, Computer Science, Economics, Mathematics, Engineering, or a related field.
* 5+ years of experience as a data Analyst, BI Analyst, or similar analytical role.
* Proficiency in SQL and experience working with relational databases.
* Hands-on experience with Databricks, Redash and other visualization tools.
* Strong analytical, problem-solving, and data storytelling skills.
* Experience with Python, or another programming language for data analysis.
* Solid understanding of data modeling, ETL processes, and data warehousing concepts.
* Excellent communication skills, with the ability to translate complex data into clear insights. Preferred Qualifications
* Experience in a global or technology-driven organization.
* Familiarity with cloud platforms (Azure, AWS, Oracle) and modern data architectures.
* Familiarity with Oracle Fusion and Oracle ADB.
* Knowledge of Machine Learning concepts and statistical modeling techniques.
* Experience with version control systems (e.g., Git) and data workflow tools (e.g., Airflow, AirByte).

Requirements:
Proven experience as a Solution Architect or in a similar role, with a strong focus on DataOps.
Deep understanding of data management principles, data modeling, and ETL processes.
Expertise in cloud technologies (AWS, Azure, GCP) and data platforms (Hadoop, Spark, Snowflake, Looker).
Strong knowledge of programming languages (Python, Java, Scala) and scripting languages (Bash, PowerShell).
Experience with DevOps tools and practices (CI/CD, containerization, orchestration).
Excellent communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
Strong problem-solving and analytical skills
Bachelors degree in Computer Science, Engineering, or a related field.
Additional Info:
Send us your CV in English and become part of WideOps team!
Only short-listed candidates will be contacted.
Confidentiality of all applications is assured!

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:
Requirements:
At least 5 years of experience in backend development/data engineering.
Experience working with SQL and NoSQL databases.
Experience with cloud development.
Working with high scale.
Ability to work in a multi-language environment.

Advantages:
B.Sc. in computer science or equivalent.
Hands-on experience with one or more of the following technologies: NodeJS, .NET Core, Kubernetes, Docker, Airflow, Data Flow and Terraform.
Hands-on experience with multiple services on Google Cloud Platform and/or Firebase.
Proven experience of hardcore performance optimization (tens of milliseconds).
TDD Experience.

Requirements:
Requirements:
Graduate with a degree in Industrial Engineering and Management or a similar major.
Experience with databases and SQL - a Must.
Outstanding technical and analytical skills.
Highly motivated with an exceptional work ethic.
High attention to detail with an ability to work on multiple projects simultaneously.
Strong interpersonal and communication skills.
Quick, self-learning capabilities and creativity in problem-solving.

Preferred:
Familiarity with Python.
Familiarity with Airflow, ETL tools, Snowflake and MSSQL.
Hands-on with VCS (Git).

Requirements:
Not sure you fit all criteria? Submit anyway, let us decide!

BSc in Computer Science, Mathematics, Engineering or a related field (MSc an advantage)
Experience in NLP - Must
3+ years of hands-on experience in research and implementation of Machine Learning based solutions
MSc in computer Science with a specialty in NLP - Big advantage
Experience in server side development, OOP language (Java/C#) Big advantage
Experience in taking NLP features to production - advantage
Experience in Deep Learning - Advantage
Strong problem solving and critical thinking skills

Requirements:
Bachelor's degree in Computer Science, Engineering, or related field
3+ years experience in data engineering
Strong proficiency in SQL and Python
Experience with ETL tools and data warehousing solutions
Knowledge of big data technologies (Hadoop, Spark, etc.)
Experience with cloud platforms (AWS, Azure, or GCP)
Understanding of data modeling and database design principles
Familiarity with data visualization tools - Tableau, Sisense
Strong problem-solving and analytical skills
Excellent communication and collaboration abilities
Experience with version control systems (Git).

Requirements:
4+ years of experience in data engineering, including cloud-based data solutions.
Proven expertise in implementing large-scale data solutions.
Proficiency in Python, SQL, PySpark is a plus.
Experience with ETL processes.
Experience with cloud and technologies such as Databricks (Apache Spark) and Azure Data factory.
Strong analytical and problem-solving skills, with the ability to evaluate and interpret complex data.
Experience leading and designing data solutions end-to-end, integrating with multiple teams, and driving tasks to completion.
Advantages :
Familiarity with either On-premise or Cloud storage systems
Excellent communication and collaboration skills, with the ability to work effectively in a multidisciplinary team.

Requirements:
4+ years of experience in SQL, data analysis and visualization
4+ years of strong scripting experience
Experience with monitoring tools such as DataDog, New Relic, Grafana, Prometheus
Understanding of statistical data
Self-learning and infinite curiosity
Strong troubleshooting and problem-solving skills
Experience with AZURE or other cloud solutions - an advantage
Kusto Query language an Advantage
Experience working with Analytics tools
Excellent teamwork skills and the ability to work autonomously
Statistical analysis experience (e.g. Python)
Experience with Artificial Intelligence - an advantage

Requirements:
5+ years of hands-on experience in backend or data engineering, including 2+ years at a senior level delivering production systems
Strong coding skills in Python, Kotlin, Java or Scala with emphasis on clean, testable, production-ready code
Proven track record designing, building and operating distributed data pipelines and storage (batch or streaming)
Deep experience with relational databases (PostgreSQL preferred) and working knowledge of at least one NoSQL or columnar/analytical store (e.g. SingleStore, ClickHouse, Redshift, BigQuery)
Solid hands-on experience with event-streaming platforms such as Apache Kafka
Familiarity with data-orchestration frameworks such as Airflow
Comfortable with modern CI/CD, observability and infrastructure-as-code practices in a cloud environment (AWS, GCP or Azure)
Ability to break down complex problems, communicate trade-offs clearly, and collaborate effectively with engineers and product partners
Bonus Skills
Experience building data governance or security/compliance-aware data platforms
Familiarity with Kubernetes, Docker, and infrastructure-as-code tools
Experience with data quality frameworks, lineage, or metadata tooling.

Requirements:
Experience working as a Data Engineer/DBA
Deep understanding of performance tuning techniques for relational databases, preferably MySQL/Vertica
Good understanding of infrastructure components, storage, networking and server hardware
Experience working with scripting/programming languages like Bash, Perl or Python
Ability to programmatically build tools that will help the team with its day-to-day tasks
Self motivated, eager to learn, loves challenges
Able to work independently
Excellent English
It Would Be Great If You Also Have:
In-depth Linux system knowledge
Vertica/HBase/Cassandra/Elastic Experience
Hands-on experience with NoSQL databases
Working experience with queuing systems, preferably Kafka
Experience in web facing environments.

Requirements:
Experience working as a Data Engineer/DBA
Deep understanding of performance tuning techniques for relational databases, preferably MySQL/Vertica
Good understanding of infrastructure components, storage, networking and server hardware
Experience working with scripting/programming languages like Bash, Perl or Python
Ability to programmatically build tools that will help the team with its day-to-day tasks
Self motivated, eager to learn, loves challenges
Able to work independently
Excellent English
It Would Be Great If You Also Have:
In-depth Linux system knowledge
Vertica/HBase/Cassandra/Elastic Experience
Hands-on experience with NoSQL databases
Working experience with queuing systems, preferably Kafka
Experience in web facing environments.

Requirements:
Experience working as a Data Engineer/DBA
Deep understanding of performance tuning techniques for relational databases, preferably MySQL/Vertica
Good understanding of infrastructure components, storage, networking and server hardware
Experience working with scripting/programming languages like Bash, Perl or Python
Ability to programmatically build tools that will help the team with its day-to-day tasks
Self motivated, eager to learn, loves challenges
Able to work independently
Excellent English
It Would Be Great If You Also Have:
In-depth Linux system knowledge
Vertica/HBase/Cassandra/Elastic Experience
Hands-on experience with NoSQL databases
Working experience with queuing systems, preferably Kafka
Experience in web facing environments.

Requirements:
What We're Looking for (Minimum Qualifications)

4+ years of experience as a Backend Engineer/Data Engineer, building data pipelines and handling high-scale data loads
Experience in backend development with expertise in one or more programming languages, such as Java, Python, Node.js, C#, or similar technologies
Good knowledge and experience with SQL
Experience with developing SAAS products over public cloud infrastructure such as AWS, Azure, GCP
B.Sc./M.Sc. in Engineering, Computer Science or relevant field, or graduate of a technical unit in the IDF
What Will Make You Stand Out (Preferred Qualifications)

Experience in Spark or equivalent (Hadoop, BigQuery, Elasticsearch etc.)
Cyber security industry experience
Software system testing methodology