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Requirements:
Job Requirements
* At least 3 years of experience and strong knowledge of Linux operating systems - mandatory
* Hands-on experience with at least one of the following technologies: PostgreSQL, MySQL, MongoDB, or Kafka - mandatory
* Familiarity with data streaming infrastructures such as Kafka - advantage
* Experience managing databases in AWS environments - advantage
* Availability to arrive on-site when required during non-standard working hours - mandatory (excluding weekends and holidays) Required Skills
* Strong self-learning capabilities
* Excellent interpersonal and customer service skills
* Availability outside regular working hours

Requirements:
+ 3 Years of experience with analyzing data and extracting insights from it.
Experience in SQL and relational Databases.
Experience with scripting languages (Python) and data analysis frameworks (Pandas, Jupyter).
High level of analytical and problem-solving skills with strong attention to details.
Reliability in execution of complicated and long tasks, Independent and self-learning skills.
Knowledge of protocols, networking and computers communication- Nice to have

Requirements:
+ 2 Years of experience with analyzing data and extracting insights from it.
Experience in SQL and relational Databases.
Knowledge of protocols, networking and computers communication.
Experience with scripting languages (Python) and data analysis frameworks (Pandas, Jupyter).
High level of analytical and problem-solving skills with strong attention to details.
Reliability in execution of complicated and long tasks, Independent and self-learning skills.

Requirements:
2 Years of experience with analyzing data and extracting insights from it.
Experience in SQL and relational Databases.
Knowledge of protocols, networking and computers communication - must.
Understanding of cybersecurity concepts, including common threats, vulnerabilities, attack vectors, and basic defensive measures -must.
Strong research abilities in networking and security, and proficiency in extracting insights from security logs.
Familiarity with scripting languages (Python) and data analysis frameworks (Pandas, Jupyter).
High level of analytical and problem-solving skills with strong attention to details.
Reliability in execution of complicated and long tasks, Independent and self-learning skills.

Requirements:
4+ years of experience as a Data Engineer.
4+ years of Python and SQL experience.
4+ years of experience in data modeling and building scalable ELT/ETL pipelines across leading Data Warehouses (Snowflake - Preferred, Redshift, BigQuery).
3+ years of experience designing and managing automated data pipelines using Apache Airflow.
3+ years of experience developing scalable, production-grade data models with DBT.
Hands-on experience with cloud environments (AWS preferred) and big data technologies.
Strong troubleshooting and debugging skills in large-scale systems.
Proven experience packaging applications with Docker and utilizing Argo Workflows to automate, execute, and monitor containerized task sequences.
Experience with design patterns, coding best practices.
Proficiency with Git and modern source control.
Basic Linux/Unix system administration skills.
Experience with AI tools and a strong interest in continuously exploring and applying them in everyday work are highly valued.
Nice to Have:
BS/MS in Computer Science or related field.
Experience with NoSQL or large-scale DBs.
Experience with microservices architecture.
Familiarity with Airbyte or other modern ETL platforms.
Experience with Apache Spark or Apache Kafka and the broader Data Engineering ecosystem

Requirements:
Bachelors Degree in Science/Data Systems Management/Industrial Engineering and Management
3+ years of experience as a Data Engineer - must
Experience with SQL - must
Experience with BI tools such as Tableau, Looker or similar - must
Knowledge in data modeling and DWH design - must
Experience in developing ETL processes - must
Experience with business requirements gathering - must
Experience with scripting languages - an advantage
Good comprehension of data, and how to tell the story behind it

Requirements:
4+ years of hands-on experience working with large-scale data using SQL and Spark or BigQuery
Strong Python skills for data analysis, scripting, and building reusable workflows
Experience working with raw, imperfect data and turning it into reliable, high-quality outputs
Strong analytical and problem-solving skills, with the ability to break down open-ended or ambiguous requirements
Ability to take end-to-end ownership of data projects, from exploration to delivery
Some hands-on experience with LLM-based systems, such as running inference via APIs, experimenting with prompts, or participating in basic evaluation or testing workflows
Clear communication skills in English and experience working directly with external stakeholders
Nice to have:
Deeper hands-on experience with LLMs in production or experimentation, for example prompt engineering, batch inference, or structured evaluation using APIs such as OpenAI, Anthropic, or similar providers
Familiarity with agent frameworks or orchestration layers (for example LangChain, LlamaIndex)
Experience with LLM evaluation or monitoring workflows, including offline evals, prompt regression testing, or tools such as LangSmith, Weights & Biases, TruLens, or Ragas
Experience experimenting with open-source or local models (for example via Ollama, vLLM, or Hugging Face tooling)
Familiarity with cloud-based data infrastructure, including AWS

Requirements:
4+ years of hands-on experience working with large-scale data using SQL and Spark or BigQuery
Strong Python skills for data analysis, scripting, and building reusable workflows
Experience working with raw, imperfect data and turning it into reliable, high-quality outputs
Strong analytical and problem-solving skills, with the ability to break down open-ended or ambiguous requirements
Ability to take end-to-end ownership of data projects, from exploration to delivery
Some hands-on experience with LLM-based systems, such as running inference via APIs, experimenting with prompts, or participating in basic evaluation or testing workflows
Clear communication skills in English and experience working directly with external stakeholders
Nice to have:
Deeper hands-on experience with LLMs in production or experimentation, for example prompt engineering, batch inference, or structured evaluation using APIs such as OpenAI, Anthropic, or similar providers
Familiarity with agent frameworks or orchestration layers (for example LangChain, LlamaIndex)
Experience with LLM evaluation or monitoring workflows, including offline evals, prompt regression testing, or tools such as LangSmith, Weights & Biases, TruLens, or Ragas
Experience experimenting with open-source or local models (for example via Ollama, vLLM, or Hugging Face tooling)
Familiarity with cloud-based data infrastructure, including AWS

Requirements:
4+ years combined experience across data platforms, including 2+ years in DBA roles (MongoDB and relational, infrastructure & application).
Practical data engineering experience (Airflow preferred).
AWS experience (1+ year).
Advanced T-SQL development skills.
Proficient with Git and code management workflows.
Strong knowledge of backup, recovery, security, and data integrity.
Strong problem-solving and algorithmic thinking.
Comfortable in a fast-paced environment and meeting deadlines.
Fluent in English.
Nice to have: dbatools, Redgate SQL Toolbelt, Coralogix; CI/CD and Liquibase.

Requirements:
5+ years of hands-on software development experience
Delphi and/or PL/SQL development experience
Proven track record as a self-directed solo contributor - able to own an application end-to-end, from interviewing users for requirements through production support
Education
B.Sc. in Computer Science / Software Engineering or Practical Engineer certification in Computer Science / Software
Technical Requirements
Mandatory
Delphi development (XE2 / 2007 ver) - Windows desktop and server applications
PL/SQL development against Oracle Database (11g and above)
REST / SOAP API design and consumption; web services development
Interfacing with SaaS platforms - ERP, CRM (e.g., MS Dynamics), PLM (e.g., Oracle Agile), BPM systems
Hybrid environment experience - on-premises + cloud (Azure, AWS, GCP)
SQL Server/SSIS/SSRS - queries, stored procedures, data modelling
Version control (Git), CI/CD experience, documentation discipline
Significant Advantage
Experience in at least one of the following: Python, .NET/C#, Node.js, or React
Windows Services, server processes, multithreading, scheduled jobs
BarTender labeling integration
LLM integration - API-based or agent frameworks, prompt engineering, MCP server development
AI-assisted development workflows (e.g., GitHub Copilot, Claude Code, Cursor, etc.)
Power BI or equivalent BI tooling - dashboards, data models, DAX / M queries
Additional Qualifications
Object-oriented design, design patterns, code maintainability in long-lived codebases.
Ability to work independently and within a team; strong interpersonal and communication skills.
Analytical thinking, problem-solving orientation, attention to detail.