Database Specialist for Graph and Time Series Data

4 weeks ago

Plano, Texas, United States Futran Tech Solutions Pvt. Ltd. Full time
Job Title: Graph and Time Series Database Specialist

Futran Tech Solutions Pvt. Ltd. is seeking a highly skilled and motivated Graph and Time Series Database Specialist to join our dynamic team.

Key Responsibilities:
  • Database Design and Implementation: Collaborate with cross-functional teams to understand data requirements and design appropriate graph and time series database schemas. Implement and configure graph and time series databases to meet specific application needs, ensuring data integrity, consistency, and security across databases.
  • Query Optimization and Performance Tuning: Analyze and optimize query performance for graph traversal and time series data retrieval. Identify and resolve bottlenecks to improve overall database performance, monitoring and fine-tuning database parameters to enhance system efficiency.
  • Data Modeling: Develop and maintain data models for graph and time series data structures, mapping complex relationships and hierarchies for efficient graph traversals. Define retention policies and storage strategies for time series data.
  • Data Integration: Integrate graph and time series databases with existing systems and applications, implementing data pipelines for seamless data ingestion and synchronization. Work with ETL processes to ensure timely and accurate data updates.
  • Security and Compliance: Implement security measures to protect sensitive data stored in the graph and time series databases, ensuring compliance with relevant data protection regulations and industry standards.

Required Qualifications:

  • Bachelor's degree in computer science, Information Technology, or a related field.
  • Proven development experience with graph database technologies (e.g., Neo4j, Amazon Neptune), time series databases (e.g., InfluxDB, TimescaleDB, AWS Timestream), NOSQL (e.g., AWS DynamoDB, MongoDB), and in-memory (e.g., AWS MemoryDB for Redis).
  • Graph query languages like openCypher, Gremlin, or SPARQL.
  • Proficiency in Python programming.
  • Solid knowledge of graph database concepts, including graph data modeling, traversal algorithms, etc.
  • Experience in graph DB tuning techniques, such as partitioning and sharding, creating and using indexes, query profiling, configuring the page cache, configuration parameters, and memory tuning, garbage collection, etc.
  • Implement data ingestion pipelines to efficiently capture and store real-time and historical time series data from various sources.
  • Design and develop time series database architectures that efficiently manage high-frequency, chronological data.
  • Proficiency in database design, query optimization, and performance tuning.
  • Strong understanding of data modeling principles for graph structures and time-based data.
  • Familiarity with real-time data processing frameworks (e.g., Kafka, Apache Flink) is a plus.
  • Excellent problem-solving and troubleshooting skills.
  • Strong communication and collaboration abilities.
  • Ability to work independently and manage multiple tasks simultaneously.
  • Preferred certifications: Neo4j Certified Professional, InfluxData Certified Professional, etc.

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