Senior Data Reliability Engineer
About the Role:
As a Senior Data Reliability Engineer, you will be responsible for architecting, scaling, and optimizing enterprise-grade data platforms, including large-scale data lakes and data warehouses built from multiple disparate data sources. This role requires deep expertise in cloud databases, data infrastructure reliability, observability, and automation, with a strong focus on operational excellence, performance, and resilience.
Responsibilities:
- Own the reliability, availability, scalability, and performance of PostgreSQL RDS environments across production and non-production systems.
- Lead proactive monitoring and observability initiatives for PostgreSQL RDS instances, leveraging tools such as CloudWatch, Prometheus, Grafana, and other enterprise monitoring platforms.
- Drive advanced PostgreSQL performance tuning, including query optimization, indexing strategies, parameter tuning, and capacity planning.
- Architect and optimize database backup, disaster recovery, and failover strategies to ensure business continuity and minimal downtime.
- Own the reliability and operational excellence of Debezium and Kafka Connect ecosystems, ensuring robust real-time data ingestion and delivery.
- Lead troubleshooting and optimization of ETL workflows and data pipelines, ensuring scalability, reliability, and fault tolerance across data platforms.
- Oversee Apache Airflow workflow orchestration, ensuring high reliability, SLA adherence, and operational efficiency of production DAGs.
- Design and implement Infrastructure as Code (IaC) solutions using tools such as Terraform, Crossplane, and automation frameworks to streamline deployments and operational tasks.
- Lead incident response, root cause analysis, and post-incident reviews for critical production issues.
- Define and enforce database security standards, including access controls, encryption policies, compliance adherence, and periodic security audits.
- Partner closely with engineering, DevOps, and data platform teams to optimize data architecture and improve overall platform reliability.
- Mentor junior engineers and drive best practices across database reliability engineering and cloud data operations.
- Identify and lead continuous improvement initiatives focused on reliability, automation, scalability, and operational maturity.
Skills:
- Deep expertise in PostgreSQL administration and performance tuning, preferably in AWS RDS environments.
- Strong experience with Debezium, Kafka Connect, ETL frameworks/tools, and enterprise-grade data pipeline architectures.
- Strong hands-on experience with Amazon Redshift, S3, and cloud-native data platforms.
- Expertise in Apache Airflow workflow orchestration and operational management.
- Experience with Apache Spark and large-scale distributed data processing.
- Strong scripting and automation experience using Python, Bash, or similar languages.
- Strong experience in Infrastructure as Code (IaC) using Terraform, Crossplane, or equivalent tools.
- Hands-on experience with monitoring and observability tools such as CloudWatch, Prometheus, Grafana.
- Strong understanding of cloud database security, compliance, and governance frameworks (e.g., GDPR, HIPAA).
- Experience designing highly available, fault-tolerant, and scalable cloud database systems.
Experience and Qualifications:
- Bachelor’s degree in computer science, Information Technology, or a related field (master’s preferred).
- 10–12 years of overall experience in database engineering, cloud data infrastructure, or reliability engineering.
- Minimum 5+ years of hands-on experience with PostgreSQL, including AWS RDS administration.
- Strong experience in cloud-native data platforms and enterprise-scale production environments.
- AWS Certified Database - Specialty or relevant cloud certifications preferred.
Skills
- AI
- Airflow
- Authentication
- Automation
- AWS
- Bash
- Cloud
- Cloud Native
- CloudWatch
- Conversational AI
- Data Ingestion
- Data Pipelines
- Debezium
- DevOps
- ETL
- Gdpr
- Grafana
- Hipaa
- Infrastructure as Code
- Kafka
- Observability
- PostgreSQL
- Prometheus
- Python
- RDS
- Redshift
- Root Cause Analysis
- S3
- Spark
- Terraform
- Workflow Orchestration
As published by lever · 12 questions · 2 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL, Github / Stack Overflow URL, Portfolio URL, Other website
Short answers (8)
- What is your current designation/title?
- What's your current location (state)?
- Are you comfortable working from Basking Ridge, New Jersey?
- Excepted CTC (per annum)
- Please provide the exact validity/expiry date of your current visa/work authorization (DD/MM/YYYY).
- How many years of hands-on experience do you have managing PostgreSQL in a production environment?
- Years of hands-on experience with Amazon Redshift?
- Experience managing ETL pipelines in production
Pick from a list (2)
- What best describes your current role?
- What is your current U.S. work authorization status?
Written answers (2)
- Have you worked on AWS RDS PostgreSQL? If yes, please briefly describe your roles and responsibilities.
- What monitoring tools have you used to monitor production AWS RDS instances?