Database Engineer

We are looking for a Database Engineer (L5) who is a senior technical contributor responsible for designing, implementing, and optimizing database systems that support distributed, cloud-native, and high-performance applications. With 5–8 years of experience, this role blends deep technical expertise with cross-functional collaboration, ensuring secure, scalable, fault-tolerant, and high-availability data platforms.

You will partner closely with software engineering, infrastructure, data engineering, and product teams to architect database schemas, optimize performance, manage data pipelines, enforce compliance, and ensure long-term reliability across environments. This role provides leadership in data modeling, query optimization, database automation, observability, and operational excellence.

Core Responsibilities:

• Design, configure, and maintain relational and NoSQL database systems across cloud and containerized environments.

• Develop and optimize schemas, indexes, queries, and stored procedures for performance, scalability, and reliability.

• Implement backup/restore strategies, high-availability configurations, replication, and disaster recovery plans.

• Troubleshoot database performance issues using profiling, monitoring, and observability tools.

• Collaborate with engineering teams to optimize data access patterns, API integrations, and application-database interactions.

• Automate provisioning, patching, schema migrations, and operational workflows using modern DevOps/DBOps practices.

• Ensure data governance, security, encryption, auditing, and compliance with regulatory requirements.

• Build and maintain CI/CD pipelines for database changes across environments.

• Participate in incident response and root-cause analysis for production data issues.

• Mentor junior engineers on database design, performance tuning, and operational best practices.

Required qualifications:

• 5–8 years of professional experience in database engineering, data platform engineering, or backend engineering with an emphasis on data systems.

• Strong expertise in one or more RDBMS technologies (PostgreSQL, MySQL, SQL Server, Aurora.

• Experience with NoSQL platforms such as MongoDB, Cassandra, DynamoDB, Redis, or Elasticsearch.

• Proficiency in SQL query optimization, indexing strategies, partitioning, and data modeling.

• Familiarity with Kubernetes-based environments, operators, StatefulSets, and persistent storage solutions.

• Hands-on experience with database observability: metrics, logs, traces, dashboards, and profiling.

• Knowledge of CI/CD pipelines, schema migration tools, and Git-based workflows.

• Understanding of cloud platforms (AWS, Azure, GCP), networking, IAM, and managed database services.

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

• Advanced English level (written and spoken) to communicate effectively across global teams.

Preferred experience:

• Experience supporting distributed or high-throughput systems in enterprise or regulated industries (healthcare, life sciences, medical devices, finance).

• Exposure to event-driven architectures, streaming platforms (Kafka, Pulsar), and CDC pipeline design.

• Familiarity with infrastructure automation (Terraform, Pulumi, Ansible) and monitoring suites (Prometheus, Grafana, Loki, OTEL).

• Experience with data warehousing (BigQuery, Snowflake, Redshift) or analytical modeling.

• Certifications in cloud architecture, database administration, or Kubernetes.

Technical skills

Database engineers at this level are expected to demonstrate familiarity with one or more tools and technologies in each of the following categories:

• Database Platforms

  • PostgreSQL, MySQL, SQL Server, Aurora, MariaDB

  • MongoDB, Cassandra, DynamoDB, Redis, Elasticsearch

• Cloud, Infrastructure & Storage

  • AWS RDS, Aurora, DynamoDB; Azure SQL, Cosmos DB; GCP Cloud SQL, Bigtable

  • Kubernetes storage (PV/PVC, StatefulSets, Longhorn)
    Backup/restore automation and HA/DR architectures

• Automation & DevOps

  • Liquibase, Flyway, Alembic for schema migrations

  • Terraform, Pulumi, Ansible

  • GitHub Actions, GitLab CI, ArgoCD, Jenkins

• Observability & Performance

  • Query planners, EXPLAIN/ANALYZE, pg_stat views

  • Prometheus, Grafana, Loki, OpenTelemetry

  • Slow-query analysis, performance tuning, index optimization

• Security & Governance

  • Data encryption (at-rest, in-transit)

  • IAM/RBAC, secret management (Vault, KMS)

  • Auditing, logging, data retention policies

Soft Skills

• Strong analytical and diagnostic skills with ability to resolve complex technical issues.

• Clear communication, especially when translating database constraints to engineering and product teams.

• Ability to collaborate across teams and influence system design decisions.

• Ownership mindset with a focus on stability, reliability, and long-term maintainability.

• Adaptability to shifting priorities in fast-paced environments.

• Mentorship capability and willingness to support junior contributors.

Organizational Competencies

• Remote Collaboration: Works effectively in distributed teams using asynchronous communication.

• Continuous Learning: Actively explores new models, frameworks, and safety techniques.

• Cultural Fit: Embodies Veritas Automata’s values of innovation, integrity, and ownership.

• Strategic Impact: Contributes reusable AI building blocks that accelerate future product delivery.

Workplace Conditions and Physical Expectations

• Prolonged periods of sitting at a desk and working on a computer.

• Must be able to lift 15 pounds at times.

• Must access and navigate each department at the organization’s facilities.

• Occasional travel to the client’s site may be required.

Work-life integration: We support work-life balance and create greater synergy among work, home, family, and personal well-being.