Demonstrated experience in utilizing Python for data engineering tasks, including transformation, advanced data manipulation, and large-scale data processing.
Hands-on experience with big data technologies including Apache Spark, Hadoop, and Kafka for distributed processing and real-time data ingestion.
Experience designing complex data pipelines extracting data from RDBMS, JSON, API, and Flat file sources.
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
Understanding of software engineering principles and skills working on Unix/Linux/Windows Operating systems, and experience with Agile methodologies.
Proficiency in version control systems, with experience in managing code repositories, branching, merging, and collaborating within a distributed development environment.
Interest in business operations and comprehensive understanding of how robust BI systems drive corporate profitability by enabling data-driven decision-making and strategic insights.
Effective oral and written English communication skills with BI team and user community.
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.
Build and optimize workflows for extracting, storing, and retrieving semantic representations of unstructured data to enable advanced search and retrieval patterns.
Architect and implement lightweight analytics and dashboarding solutions that deliver natural language query experience and AI-backed insights.
Define and execute processes for managing prompt engineering techniques, orchestration flows, and model fine-tuning routines to power conversational interfaces.
Oversee vector data stores and develop efficient indexing methodologies to support retrieval-augmented generation (RAG) workflows.
Partner with data stakeholders to gather requirements for language-model initiatives and translate into scalable solutions.
Create and maintain comprehensive documentation for all data processes, workflows and model deployment routines.
Should be willing to stay informed and learn emerging methodologies in data engineering, MLOps and LLM operations.
Remote work opportunity!
B2B Employment ($, gross).
Stable job with long-term growth perspective with talented people around.
Really good hardware.
Great learning and growth opportunities.
Compensation for professional training, seminars, and conferences.
Referral program – get rewarded for helping us grow the team with talented people.
Company-supported English classes to enhance your professional growth.
