Neysa.ai - Database Administrator (7-12 yrs)

Key Responsibilities :

- Data Pipeline Management : Design, implement, and manage robust data pipelines to ensure seamless data flow between systems for AI models and machine learning workloads.

- Database Reliability & Optimization : Oversee the reliability, availability, and performance of databases and data stores across the platform. Tune and optimize queries, schema, and configurations for improved performance.

- Data Security & Compliance : Implement data security measures to protect sensitive information, ensuring compliance with data privacy regulations and company policies.

- Collaboration with AI Teams : Work closely with Data Science and ML teams to ensure data is accessible, clean, and in the right format for model training and inference.

- Monitoring & Troubleshooting : Continuously monitor the health of data pipelines and databases. Quickly troubleshoot and resolve performance bottlenecks or system failures.

- Automation & Optimization : Develop automated solutions for data pipeline operations, reducing manual intervention and ensuring high scalability and low latency.

- Documentation : Maintain clear documentation of database architecture, data pipelines, and troubleshooting processes for cross-team collaboration.

Must have skills :

- Database Administration : 4-8 years of experience managing relational databases (PostgreSQL, MySQL, or similar), including backup, recovery, performance tuning, and high availability solutions.

- Data Pipeline Development : Solid experience in building and managing scalable data pipelines using tools like Apache Kafka, Apache Airflow, or other ETL frameworks.

- Experience on management of Elastic

- Ability to configure and run the Postgres, Kafka and Elastic Clusters,

- Security Practices : Expertise in implementing data encryption, access controls, and security policies to ensure the safety of sensitive data within databases and pipelines.

- SQL & Query Optimization : Proficiency in writing complex SQL queries and optimizing database performance for large datasets and high-velocity transactions.

- Problem-Solving & Troubleshooting : Strong analytical and troubleshooting skills to diagnose and resolve system and data pipeline issues in real-time.

Good to have :

- If you know any of the graph and time series databases like Neo4J and Timescale DB it would be awesome.

- NoSQL Databases: Familiarity with NoSQL databases such as MongoDB, or Redis for handling unstructured data.

- AI/ML Collaboration: Experience working closely with AI/ML teams to support data requirements for model training and production environments.

- Big Data Technologies: Familiarity with big data tools like Apache Hadoop, Spark, or related technologies for handling large-scale data processing.

- Scripting: Proficiency in scripting languages like Python, Bash, or similar for automating tasks and developing custom solutions.

Technical Skills :

- Databases : PostgreSQL, MySQL, Elastic

- Data Pipeline Tools : Apache Kafka, or similar ETL frameworks

- Security : Data encryption, IAM (Identity and Access Management), access control policies

- Programming/Scripting : SQL, Python, Bash, or similar languages for automation

- Monitoring & Logging : Prometheus, Grafana, ELK Stack, CloudWatch

- NoSQL : MongoDB, Neo4j, Timescale DB, Redis

- Big Data : Apache Spark, Hadoop, Flink