Senior Data Platform Engineer

4 days ago

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Software Mind

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Artificial Intelligence • SaaS • Telecommunications

Software Mind is a technology company that specializes in software development and digital transformation services. With a focus on AI and cloud solutions, the company offers a wide range of services including custom software development, mobile app development, and cloud consulting. Software Mind serves various industries such as financial services, telecom, biotech, and media, providing tailored solutions to accelerate digital transformations and business growth globally.

1001 - 5000 employees

Founded 1999

🤖 Artificial Intelligence

☁️ SaaS

📡 Telecommunications

💰 Private Equity Round on 2020-12

📋 Description

• Design, implement, and maintain scalable data storage solutions across SQL, NoSQL, in-memory, and search systems. • Ensure high availability, resilience, and observability across all data systems. • Identify and resolve performance bottlenecks across the data layer. • Implement caching, indexing, partitioning, and load-distribution strategies for large-scale data. • Support AI-driven features by ensuring data systems provide efficient access to structured and unstructured sources. • Assist in implementing vector storage, semantic indexing, or future RAG (Retrieval Augmented Generation) capabilities. • Use AI-assisted tools to analyze system performance, generate code, and improve data architecture documentation. • Partner with backend engineers to design data interactions that align with system and API requirements. • Document data systems, schemas, standards, and patterns. • Provide technical mentoring on data practices, observability, and AI-assisted tooling.

🎯 Requirements

• +90% English written and oral (at least C1 level) with excellent communication skills. • 5+ years of experience managing or engineering large-scale data systems. • Strong understanding of SQL, NoSQL, and distributed data storage technologies. • Proven experience with MSSQL, MongoDB, Redis, or similar systems. • Familiarity with search indexing tools (Elasticsearch, Solr) and high-performance data retrieval patterns. • Experience with data modeling, normalization/denormalization, and schema evolution. • Proficiency with observability tools and monitoring platforms. • Experience with AI-assisted development tools (e.g., GitHub Copilot, ChatGPT). • Knowledge of cloud-native data infrastructure (AWS or Azure). • Experience with vector databases, embedding-based indexing, or semantic retrieval. • Background in event-driven or streaming architectures (Kafka, EventBridge, etc.). • Communicates clearly and collaborates across engineering and product teams.

🏖️ Benefits

• Educational resources. • Flexible schedule and Work From Anywhere. • Referral Program. • Supportive and chill atmosphere.