Senior Data Engineer 1

We are seeking a highly skilled and experienced Senior Data Engineer with strong Development DBA expertise to design, develop, implement, optimize, and support enterprise-scale database solutions across Relational and NoSQL database platforms.

The ideal candidate will have extensive hands-on experience managing the end-to-end database development lifecycle, from requirements gathering, data modeling, and logical/physical database design through database development, deployment, performance tuning, optimization, and production implementation.

This role requires deep technical expertise across PostgreSQL, Oracle, Cassandra, Couchbase, Microsoft SQL Server, and IBM Db2 LUW, along with experience designing and implementing database solutions in AWS and/or Google Cloud Platform (GCP) environments.

The candidate will collaborate closely with application development teams, solution architects, infrastructure teams, and business stakeholders to deliver scalable, secure, resilient, and high-performing database solutions aligned with enterprise architecture standards.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline, or equivalent practical experience.
• 10+ years of hands-on experience in database engineering, database development, or Development DBA roles within enterprise environments.
• Demonstrated experience owning end-to-end database development activities, from requirements analysis and logical/physical design through deployment and performance optimization.
• Strong expertise in SQL development, query optimization, database schema design, indexing, and execution plan analysis.
• Hands-on engineering experience with multiple database technologies, including PostgreSQL, Oracle, Microsoft SQL Server, IBM Db2 LUW, Cassandra, and Couchbase.
• Deep expertise in at least two relational database platforms, with the ability to work across additional database technologies.
• Practical experience designing and optimizing NoSQL database solutions.
• Hands-on experience with database services and engineering practices in AWS and/or GCP.
• Experience implementing database changes through automated DB CI/CD pipelines and schema migration frameworks.
• Strong understanding of database internals, transaction management, concurrency, locking, indexing, partitioning, and query optimization.
• Strong analytical, troubleshooting, technical documentation, and cross-functional communication skills.

Preferred Qualifications

• Experience in large-scale enterprise, financial services, or other highly regulated environments.
• Experience with high-volume OLTP systems, mission-critical applications, and distributed database architectures.
• Experience with cloud database modernization, migration, and hybrid-cloud architectures.
• Knowledge of database replication, high availability, disaster recovery, and backup/recovery design principles.
• Experience with infrastructure automation using Terraform or similar tools.
• Familiarity with database observability and monitoring solutions.
• Experience with data integration, ETL/ELT pipelines, and data engineering frameworks.
• Knowledge of data governance, data security, and regulatory compliance practices.
• Experience conducting database architecture assessments, performance benchmarking, and capacity planning.

Key Responsibilities

1. End-to-End Database Engineering Lifecycle

• Own and drive the complete database development lifecycle, from initial requirements gathering through design, development, testing, deployment, optimization, and ongoing enhancements.
• Collaborate with business stakeholders, application teams, and solution architects to translate functional and non-functional requirements into robust database solutions.
• Develop database architecture specifications, technical design documents, data models, and implementation strategies.
• Lead database design reviews, code reviews, and technical solution assessments.
• Ensure database solutions meet enterprise standards for scalability, availability, performance, security, and maintainability.

2. Data Modeling and Database Design

• Design and develop conceptual, logical, and physical data models for Relational and NoSQL database platforms.
• Apply appropriate data modeling methodologies, including normalization, denormalization, indexing, partitioning, and data distribution strategies.
• Design database objects including tables, relationships, constraints, views, indexes, and other database objects.
• Develop efficient data access patterns and storage models based on application workloads and business requirements.
• Evaluate database technology choices and recommend optimal relational or NoSQL solutions based on workload characteristics.
• Define database standards, naming conventions, data integrity controls, and design best practices.

3. Database Development and Engineering

• Implement database solutions across PostgreSQL, Oracle, SQL Server, Db2 LUW, Cassandra, and Couchbase.
• Design and implement efficient transaction processing, concurrency handling, and data access mechanisms.
• Partner with application development teams to optimize database integration and application-to-database interactions.
• Build reusable database components, development frameworks, and automation utilities.

4. Database Performance Engineering and Optimization

• Perform proactive and reactive database performance tuning across relational and NoSQL platforms.
• Analyze SQL execution plans, query performance metrics, database statistics, and workload characteristics to identify performance bottlenecks.
• Optimize query execution, indexing strategies, partitioning, memory utilization, concurrency, and database configurations.
• Diagnose and resolve issues involving locking, blocking, deadlocks, inefficient queries, and resource contention.
• Conduct database workload analysis, performance benchmarking, capacity planning, and scalability assessments.
• Collaborate with application teams to improve end-to-end application and database performance.

5. Database Deployment, DevOps, and Automation

• Design and implement automated database deployment and release management processes.
• Integrate database schema changes, SQL scripts, and configuration updates into CI/CD pipelines.
• Implement database version control, schema migration, release validation, and rollback strategies.
• Utilize tools including Liquibase, Git, GitHub Actions, or equivalent enterprise DevOps platforms.
• Develop automation using Python, Shell scripting, and Infrastructure as Code technologies such as Terraform.
• Establish repeatable, auditable, and reliable database deployment processes across development, testing, staging, and production environments.

6. Cloud Database Engineering – AWS / GCP

• Design, develop, deploy, and optimize database solutions hosted in AWS and/or Google Cloud Platform.
• Work with managed database services such as:
  • AWS: Amazon RDS, Amazon Aurora, DynamoDB and applicable cloud-native database services.
  • GCP: Cloud SQL, AlloyDB, Spanner, and other relevant managed database offerings.
• Evaluate and implement cloud database architecture patterns for high availability, scalability, disaster recovery, and cost optimization.
• Support database modernization and migration initiatives from on-premises infrastructure to public cloud platforms.
• Implement cloud-native database monitoring, security, configuration management, and automation practices.
• Collaborate with cloud architecture and platform engineering teams to define database provisioning and operational standards.

7. NoSQL Database Engineering

• Design and optimize distributed NoSQL database solutions using Cassandra and Couchbase.
• Develop data models aligned with application access patterns, partitioning strategies, and distributed data architectures.
• Optimize Cassandra partition keys, clustering keys, replication strategies, and query patterns.
• Design Couchbase document structures, indexes, N1QL/SQL++ queries, and data access patterns.
• Understand distributed database concepts, including consistency models, replication, fault tolerance, and horizontal scalability.
• Diagnose and resolve NoSQL performance, data distribution, and application integration issues.

8. Database Reliability, Security, and Production Readiness

• Engineer database solutions with appropriate availability, recoverability, resiliency, and disaster recovery considerations.
• Incorporate security requirements such as encryption, access controls, least-privilege access, and sensitive data protection into database designs.
• Support database security and compliance requirements in regulated enterprise environments.
• Conduct database production readiness assessments, deployment risk reviews, and performance validations.
• Partner with Production DBA, SRE, and infrastructure teams on production implementation, incident resolution, and root cause analysis.
• Establish monitoring, observability, and operational handoff requirements for database solutions.

9. Technical Leadership and Collaboration

• Serve as a subject matter expert for database development DBA practices, and database performance optimization.
• Provide technical guidance and mentorship to database engineers and application development teams.
• Influence database architecture decisions, technology selection, and engineering best practices.
• Drive continuous improvements in database design, development standards, automation, and engineering productivity.
• Collaborate across architecture, application development, cloud engineering, cybersecurity, and production support teams.