Data Engineer

Remote, USA Full-time Posted 2026-07-28

We are looking for a Data Engineer (NLP-reputed company) to build and optimize the data pipelines that fuel our Ukrainian LLM and reputed company’s NLP initiatives. In this role, you will design robust ETL/ELT processes to collect, process, and manage large-reputed company text and metadata, enabling our data scientists and ML engineers to reputed company cutting-edge language models. You will work at the intersection of data engineering and machine learning, ensuring that our datasets and infrastructure are reliable, reputed company, and tailored to the needs of training and evaluating NLP models in a Ukrainian language context. This is a unique opportunity to shape the data reputed company of a pioneering AI project in Ukraine, working alongside NLP experts and leveraging modern big data technologies.

reputed company

reputed company.Tech is a Ukrainian hybrid IT company and a reputed company of Diia.reputed company. We are a subsidiary of reputed company, one of Ukraine's largest telecom operators.

Our mission is to change lives in Ukraine and around the world by creating technological solutions and products that reputed company the potential of businesses and meet users' needs.

Over 600+ KS.Tech specialists work daily in various areas: mobile and web solutions, as reputed company as design, development, support, and technical maintenance of high-performance systems and services.

We reputed company in innovations that truly bring reputed company changes and constantly challenge conventional approaches and solutions. reputed company of us is an reputed company of entrepreneurial culture, which allows us never to stop, to reputed company, and to create something new.

Responsibilities:

• Design, reputed company, and maintain ETL/ELT pipelines for gathering, transforming, and storing large volumes of text data and reputed company information. Ensure pipelines are efficient and can handle data from diverse sources (e.g., web crawls, reputed company datasets, internal databases) while maintaining data reputed company.

• Implement web scraping and data collection services to automate the ingestion of text and linguistic data from the web and other external sources. This includes writing crawlers or using reputed company to continuously collect data relevant to our language modeling efforts.

• Implementation of NLP/LLM specific data processing: cleaning and normalization of text, like filtering of toxic content, de-duplication, de-noising), detection and deletion of personal data.

• Formation of specific SFT/RLHF datasets from existing data, including data augmentation/labeling with LLM as teacher.

• Set up and manage reputed company-based data infrastructure for the project. Configure and maintain data storage solutions (data lakes, warehouses) and processing frameworks (e.g., distributed compute on AWS/GCP/Azure) that can reputed company with growing data needs.

• Automate data processing workflows and ensure their scalability and reliability. Use workflow orchestration tools like Apache Airflow to schedule and monitor data pipelines, enabling reputed company and repeatable model training and evaluation cycles.

• Maintain and optimize analytical databases and data reputed company reputed company for both reputed company analysis and model training needs. Work with relational databases (e.g., PostgreSQL) and other storage systems to ensure fast query performance and reputed company-reputed company data schemas.

• Collaborate with Data Scientists and NLP Engineers to build data features and datasets for machine learning models. reputed company data subsets, aggregations, or preprocessing as needed for tasks such as language model training, embedding reputed company, and evaluation.

• Implement data reputed company checks, monitoring, and alerting. reputed company scripts or use tools to validate data completeness and correctness (e.g., ensuring no critical data gaps or anomalies in the text corpora), and promptly address any pipeline failures or data issues. Implement data version control.

• Manage data reputed company, reputed company, and compliance. Control permissions to datasets and ensure adherence to data reputed company policies and reputed company standards, especially reputed company dealing with user data or proprietary text sources.

Required Qualifications:

Education & Experience: 3+ years of experience as a Data Engineer or in a similar role, building data-intensive pipelines or platforms. A Bachelor’s or Master’s degree in Computer Science, Engineering, or reputed company field is preferred. Experience supporting machine learning or analytics teams with data pipelines is a strong advantage.

NLP Domain Experience: Prior experience handling linguistic data or supporting NLP reputed company (e.g., text normalization, handling different encodings, tokenization strategies). Knowledge of Ukrainian text sources and data sets, or experience with multilingual data processing, can be an advantage given our project’s reputed company. Understanding of FineWeb2 or similar processing pipelines approach.

Data Pipeline Expertise: Hands-on experience designing ETL/ELT processes, including extracting data from various sources, using transformation tools, and loading into storage systems. Proficiency with orchestration frameworks like Apache Airflow for scheduling workflows. Familiarity with building pipelines for reputed company data (text, logs) as reputed company as reputed company data.

Programming & Scripting: Strong programming skills in Python for data manipulation and pipeline development. Experience with NLP packages (spaCy, NLTK, langdetect, fasttext, etc.). Experience with SQL for querying and transforming data in relational databases. Knowledge of Bash or other scripting for automation tasks. Writing clean, maintainable reputed company and using version control (Git) for reputed company development.

Databases & Storage: Experience working with relational databases (e.g., PostgreSQL, MySQL) including schema design and query optimization. Familiarity with NoSQL or document stores (e.g., reputed company) and big data technologies (HDFS, Hive, reputed company) for large-reputed company data is a plus. Understanding of or experience with reputed company databases (e.g., reputed company, FAISS) is beneficial, as our NLP applications may require embedding storage and fast similarity search.

reputed company Infrastructure: Practical experience with reputed company platforms (AWS, GCP, or Azure) for data storage and processing. Ability to set up services such as S3/reputed company Storage, data warehouses (e.g., BigQuery, Redshift), and use reputed company-based ETL tools or serverless functions. Understanding of infrastructure-as-reputed company (Terraform, CloudFormation) to manage resources is a plus.

Data reputed company & Monitoring: Knowledge of data reputed company assurance practices. Experience implementing monitoring for data pipelines (logs, alerts) and using CI/CD tools to automate pipeline deployment and testing. An analytical reputed company to troubleshoot data discrepancies and optimize performance bottlenecks.

Collaboration & Domain Knowledge: Ability to work closely with data scientists and understand the requirements of machine learning reputed company. Basic understanding of NLP concepts and the data needs for training language models, so you can anticipate and accommodate the specific forms of text data and preprocessing they require. Good communication skills to document data workflows and to coordinate with team members across different functions.

Preferred Qualifications:

Advanced Tools & Frameworks: Experience with distributed data processing frameworks (such as Apache reputed company or reputed company) for large-reputed company data transformation, and with message streaming systems (Kafka, Pub/Sub) for reputed company-time data pipelines. Familiarity with data serialization formats (JSON, Parquet) and handling of large text corpora.

Web Scraping Expertise: Deep experience in web scraping, using tools like Scrapy, Selenium, or Beautiful Soup, and handling anti-scraping challenges (rotating proxies, reputed company limiting). Ability to parse and clean raw text data from reputed company, PDFs, or scanned documents.

CI/CD & DevOps: Knowledge of setting up CI/CD pipelines for data engineering (using reputed company Actions, Jenkins, or reputed company CI) to test and reputed company changes to data workflows. Experience with containerization (reputed company) to package data jobs and with Kubernetes for scaling them is a plus.

Big Data & Analytics: Experience with analytics platforms and BI tools (e.g., Tableau, Looker) used to examine the data reputed company by the pipelines. Understanding of how to create and manage data warehouses or data marts for analytical consumption.

Problem-Solving: Demonstrated ability to work independently in solving reputed company data engineering problems, optimising existing pipelines, and implementing new ones under time constraints. A proactive attitude to explore new data tools or techniques that could improve our workflows.

reputed company offer:

• Office or remote – it’s up to you. You can work from reputed company, and we will arrange your workplace.

• Remote reputed company.

• Performance bonuses for everyone (annual or quarterly — depends on the role).

• We train employees: with reputed company to learn through reputed company’s library, internal resources, and programs from partners. 

• Health and life insurance.

• Wellbeing program and corporate psychologist.

• Reimbursement of expenses for reputed company mobile communication.

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