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8+ years of experience as a Data Engineer.
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Demonstrated experience in utilizing Python for data engineering tasks, including transformation, advanced data manipulation, and large-scale data processing.
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Hands-on experience with big data technologies including Apache Spark, Hadoop, and Kafka for distributed processing and real-time data ingestion.
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Experience designing complex data pipelines extracting data from RDBMS, JSON, API, and Flat file sources.
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Demonstrated skills in SQL and PLSQL programming, with advanced mastery in Business Intelligence and data warehouse methodologies, along with hands-on experience in one or more relational database systems and cloud-based database services such as Snowflake/Redshift
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Understanding of software engineering principles and skills working on Unix/Linux/Windows Operating systems, and experience with Agile methodologies.
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Proficiency in version control systems, with experience in managing code repositories, branching, merging, and collaborating within a distributed development environment.
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Interest in business operations and comprehensive understanding of how robust BI systems drive corporate profitability by enabling data-driven decision-making and strategic insights.
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Effective oral and written English communication skills with BI team and user community.
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Design, develop, and maintain scalable data pipelines to support ingestion, transformation, and delivery into centralized feature stores, model-training workflows, and real-time inference services.
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Build and optimize workflows for extracting, storing, and retrieving semantic representations of unstructured data to enable advanced search and retrieval patterns.
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Architect and implement lightweight analytics and dashboarding solutions that deliver natural language query experience and AI-backed insights.
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Define and execute processes for managing prompt engineering techniques, orchestration flows, and model fine-tuning routines to power conversational interfaces.
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Oversee vector data stores and develop efficient indexing methodologies to support retrieval-augmented generation (RAG) workflows.
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Partner with data stakeholders to gather requirements for language-model initiatives and translate into scalable solutions.
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Create and maintain comprehensive documentation for all data processes, workflows and model deployment routines.
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Should be willing to stay informed and learn emerging methodologies in data engineering, MLOps and LLM operations.
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Experience with vector databases such as DataStax AstraDB, and developing LLM-powered applications using popular open source frameworks like LangChain and LlamaIndex–including prompt engineering, retrieval-augmented generation (RAG), and orchestration of intelligent workflows.
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Familiarity with evaluating and integrating open-source LLM frameworks–such as Hugging Face Transformers/LLaMA-4 across end-to-end workflows, including fine-tuning and inference optimization.
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Knowledge of MLOps tooling and CI/CD pipelines to manage model versioning and automated deployments.
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Remote work opportunity!
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B2B Employment ($, gross).
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Stable job with long-term growth perspective with talented people around.
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Really good hardware.
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Great learning and growth opportunities.
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Compensation for professional training, seminars, and conferences.
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Referral program – get rewarded for helping us grow the team with talented people.
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Company-supported English classes to enhance your professional growth.
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