Senior Data Engineer

Humain Dev Systems — Armenia · Posted ~1 day ago

Senior Full-time

Skills

data engineering SQL database optimization ETL pipelines data modeling database sharding ETL databases data warehouses IAM

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Summary ✨ AI‑Generated

A senior data engineer is needed to optimize and scale data platforms. The role covers database architecture, ETL development, data modeling, query optimization, and secure data management.

Highlights

Own and improve large-scale data infrastructure while solving performance, scalability, and reliability challenges.

Description

Description We are looking for a highly skilled Senior Data Engineer to join our team and take ownership of optimizing, scaling, and maintaining our data infrastructure. You will play a critical role in ensuring data accuracy, performance, and reliability across our systems. Responsibilities Collect, validate, and ensure the accuracy of data from multiple sourcesOptimize and restructure databases to improve efficiency and scalabilityImprove query performance with a strong focus on mission-critical queries (especially for Evidence data)Implement and manage DB sharding strategies for scalabilityDesign, develop, and maintain data models, warehouses, and ETL pipelinesWork with frequently updating, high-volume data environmentsCollaborate with product, engineering, and DevOps teams to ensure seamless data flowEnsure data security and compliance using IAM roles and permissions Required qualifications Extensive experience working with complex database structuresExpert knowledge of databases (especially MySQL)Strong background in Big Data technologies and large-scale data processingHands-on experience with data modeling, warehousing, and ETL pipelinesExperience managing frequently updating data systemsSolid understanding of query optimization and performance tuningProficiency with AWS services, Redis, IAM roles and permissionsStrong problem-solving skills and ability to work in fast-paced environmentsNice to Have Familiarity with Soft DevOps skills (CI/CD, containerization, monitoring, etc.)Exposure to modern data stack tools (Airflow, Spark, Kafka, etc.)