Torchora
Back to Home

Key Responsibilities and Required Skills for Database Engineer

💰 $95,000 - $165,000

EngineeringDataIT

🎯 Role Definition

The Database Engineer is responsible for designing, deploying, maintaining, tuning, and securing the organization's database platforms to ensure availability, scalability, performance, and data integrity. This role partners with application engineers, data engineers, DevOps, and product teams to enable reliable data access, efficient query performance, and robust disaster recovery strategies across on-premises and cloud environments (AWS, Azure, GCP). The Database Engineer contributes to data architecture, implements best practices for schema design and indexing, automates operational tasks, and enforces backup, recovery, and security controls while supporting business needs and SLAs.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Database Administrator (DBA) or Junior Data Engineer
  • Software Engineer with strong SQL and data fundamentals
  • Systems Administrator with database exposure

Advancement To:

  • Senior Database Engineer / Lead DBA
  • Data Platform Engineer / Data Architect
  • Engineering Manager, Data Infrastructure

Lateral Moves:

  • Data Engineer (ETL, pipelines, analytics)
  • Site Reliability Engineer (SRE) focusing on data services
  • Cloud Database Specialist / Cloud Architect

Core Responsibilities

Primary Functions

  • Design, implement and maintain normalized and denormalized database schemas and data models to support transactional (OLTP) and analytical (OLAP) workloads, ensuring optimal query performance, minimal data redundancy, and maintainable migrations.
  • Lead database performance tuning initiatives by profiling slow queries, analyzing execution plans, implementing advanced indexing strategies, partitioning large tables, and recommending schema changes to reduce latency and resource consumption.
  • Architect and manage high-availability database solutions including replication, clustering, automated failover, multi-AZ deployments, and read-replica strategies to meet RTO/RPO and SLA targets.
  • Plan and execute database migrations and upgrades across versions and platforms (e.g., MySQL → Amazon Aurora, on-prem PostgreSQL → RDS/Aurora, Oracle → Cloud-native) with zero/low downtime strategies and thorough rollback plans.
  • Develop, maintain and automate backup, restore, and disaster recovery processes, including full, incremental and PITR (point-in-time recovery) strategies, regularly testing restores to validate recovery objectives.
  • Implement and enforce database security best practices: access controls, least privilege, role-based access, auditing, encryption at rest and in transit, key management, and vulnerability remediation to meet compliance (SOC2, HIPAA, PCI, GDPR).
  • Build and maintain automated provisioning and configuration management for database instances using Infrastructure-as-Code tools (Terraform, CloudFormation, Ansible) to ensure consistent, auditable deployments.
  • Design and operate ETL/ELT data ingestion pipelines and integrate databases with data warehousing solutions (Redshift, BigQuery, Snowflake), streaming platforms (Kafka), and batch-processing frameworks to support analytics and reporting needs.
  • Create and own database CI/CD pipelines for schema migrations and versioned DDL/DDL changes, integrating with source control, automated tests, and rollback mechanisms to reduce deployment risks.
  • Implement monitoring, alerting and observability for database health, performance and capacity (Prometheus, Datadog, New Relic, Grafana), define SLOs/SLAs, and respond to incidents with on-call rotations and runbooks.
  • Conduct capacity planning and cost optimization for cloud-hosted databases: instance sizing, storage tiering, autoscaling patterns, and cost forecasting to balance performance and budget.
  • Execute data integrity, consistency and reconciliation processes, build checks and automated tests for data quality, and implement row-level/column-level security and masking where required.
  • Manage replication topologies and conflict resolution strategies for multi-region deployments and real-time replication to support global read performance and localized failover.
  • Collaborate with application and backend engineering teams to optimize ORM usage, parameterized queries, transaction isolation levels and to reduce N+1 patterns and inefficient data access patterns.
  • Author and maintain comprehensive runbooks, operational runbooks and postmortem documentation for database incidents, upgrades and maintenance windows.
  • Design and implement sharding strategies and horizontal partitioning for high-cardinality datasets, including key selection, re-sharding procedures and cross-shard query patterns.
  • Evaluate, recommend and pilot new database technologies (NoSQL: MongoDB, Cassandra; NewSQL: CockroachDB; cloud-native managed services) for use cases requiring specialized capabilities such as global distribution or ultra-low latency.
  • Stay current on database security patches, engine releases and configuration hardening; schedule and manage patch windows and compatibility testing for internal applications.
  • Lead SQL code reviews and mentor engineers on efficient query writing, index design, table statistics management and effective use of stored procedures and triggers where appropriate.
  • Implement observability for long-running transactions, deadlock detection and mitigation, and proactively resolve blocking/locking issues to minimize production impact.
  • Partner with data governance and privacy teams to implement data lineage, retention policies, archival strategies, and anonymization/pseudonymization techniques for regulated data.
  • Design testing strategies for database changes including unit tests for migration scripts, integration tests against representative data volumes and performance benchmarks to validate changes before production rollout.
  • Optimize backup retention policies, tier archival storage, and implement lifecycle management for historical data while providing access for analytics and regulatory audits.
  • Serve as primary technical owner for database-related incidents, lead the triage process, coordinate cross-functional remediation, and produce clear incident reports and follow-up action plans.
  • Drive standardization of database tooling, templates, and playbooks to accelerate provisioning, reduce configuration drift, and enable consistent governance across engineering teams.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Provide periodic training and best-practice workshops for application developers on SQL performance and efficient schema usage.
  • Maintain an up-to-date inventory of database assets, licenses, and configuration baselines to support audits and vendor management.

Required Skills & Competencies

Hard Skills (Technical)

  • Advanced SQL expertise: complex query optimization, window functions, CTEs, query plan analysis and index selection.
  • Relational databases: deep experience with PostgreSQL, MySQL/MariaDB, SQL Server or Oracle internals and administration.
  • NoSQL and distributed databases: practical knowledge of MongoDB, Cassandra, DynamoDB or other document/column-family stores where applicable.
  • Cloud-managed databases and services: AWS RDS/Aurora, Amazon Redshift, Google Cloud SQL/Spanner, Azure SQL Database, and Teired storage management.
  • Performance tuning: index maintenance, partitioning strategies, vacuuming, statistics management, and execution plan analysis.
  • Backup & recovery and disaster recovery (DR): PITR, replication-based failover, backup encryption, and restore validation.
  • Data modeling and schema design for OLTP and OLAP systems; dimensional modeling for data warehouses.
  • ETL/ELT tools and pipeline integration: Airflow, Fivetran, Talend, Informatica, dbt or similar orchestration and transformation tools.
  • Automation and IaC: Terraform, CloudFormation, Ansible, or similar for provisioning and configuration management.
  • Scripting and automation: Python, Bash, PowerShell for automation, health checks, and ad-hoc data tasks.
  • Monitoring and observability: Prometheus, Grafana, Datadog, New Relic, or native cloud monitoring tools for alerting and dashboards.
  • CI/CD for database changes: experience with Liquibase, Flyway, or custom migration pipelines and test automation.
  • Security and compliance: role-based access control, encryption, auditing, vulnerability scanning and privacy regulations (GDPR/CCPA).
  • Containerization and orchestration: Docker and Kubernetes for running database tools, sidecars, or local development environments.
  • Familiarity with replication, clustering and distributed consensus (e.g., multi-master, leader-follower) and their operational tradeoffs.

Soft Skills

  • Strong analytical and problem-solving skills with a methodical approach to incident triage and root cause analysis.
  • Excellent communication skills capable of translating technical concepts for stakeholders, providing clear incident reports and runbooks.
  • Collaboration and influence across cross-functional teams (engineering, security, product, operations) with a customer-first mindset.
  • Time management and prioritization skills to balance operational SLAs, projects and technical debt.
  • Mentorship and knowledge-sharing orientation to upskill engineering peers and drive continuous improvement.
  • Flexibility and resilience in on-call rotations and high-pressure incident response situations.
  • Strategic thinking with the ability to align database roadmap decisions to business goals and cost constraints.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or equivalent technical field — or equivalent practical experience.

Preferred Education:

  • Master's degree in Computer Science, Data Engineering, or related discipline.
  • Relevant certifications: AWS Certified Database Specialty, Google Professional Data Engineer, Microsoft Azure Database Administrator Associate, or vendor-specific DBA certifications.

Relevant Fields of Study:

  • Computer Science
  • Information Systems
  • Software Engineering
  • Data Engineering / Data Science
  • Applied Mathematics or Statistics

Experience Requirements

Typical Experience Range: 3–8+ years of hands-on experience managing production databases, implementing performance optimizations, and executing cloud migrations.

Preferred:

  • 5+ years as a Database Engineer, Senior DBA, or Data Platform Engineer responsible for mission-critical production systems.
  • Proven experience with at least two major relational databases (e.g., PostgreSQL and MySQL) and one cloud-managed database service.
  • Track record of successful database migrations (on-prem → cloud or cross-engine), implementing HA/DR architectures, and running on-call rotations.
  • Demonstrated experience with automation, IaC, CI/CD for database changes, and performance benchmarking at scale.
Explore More Careers