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Key Responsibilities and Required Skills for Database Programmer

💰 $70,000 - $120,000

ITDatabaseSoftware DevelopmentData Engineering

🎯 Role Definition

A Database Programmer is responsible for designing, developing, optimizing and maintaining the database layer of applications and data platforms. This role focuses on writing efficient SQL and procedural code (T-SQL, PL/SQL), building and optimizing stored procedures, functions and triggers, implementing ETL and data integration pipelines, ensuring data integrity and security, and collaborating closely with application developers, data engineers and business stakeholders to deliver reliable, high-performance data solutions both on-premises and in cloud environments.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Junior Database Developer / SQL Developer
  • Software Developer with SQL experience
  • ETL / BI Developer

Advancement To:

  • Senior Database Developer / Senior SQL Engineer
  • Database Administrator (DBA) / Senior DBA
  • Data Engineer / Lead Data Engineer
  • Data Architect / Solutions Architect

Lateral Moves:

  • Business Intelligence Engineer
  • Application Developer (full-stack/backend)
  • DevOps Engineer with database focus

Core Responsibilities

Primary Functions

  • Design, develop and maintain complex SQL queries, stored procedures, functions, views and triggers to support application features, reporting and analytics with an emphasis on readability, maintainability and performance.
  • Analyze, profile and optimize slow-running queries, execution plans and database resource usage (CPU, memory, I/O) to improve transaction throughput and reduce latency in OLTP and OLAP systems.
  • Build and maintain ETL pipelines and data ingestion processes using tools such as SSIS, Talend, Informatica, or custom Python/SQL scripts to reliably move, transform and validate data between systems.
  • Model and refine relational database schemas, normalize/denormalize tables where appropriate, establish foreign keys and constraints, and document logical and physical data models.
  • Design and implement indexing strategies (clustered, non-clustered, filtered, covering indexes) and partitioning schemes to support large tables and improve query performance.
  • Create and enforce database coding standards, naming conventions and documentation for schema changes, migrations and stored code to support team consistency and code review processes.
  • Implement and maintain database version control and deployment pipelines using Git, CI/CD tools (Jenkins, GitLab CI, Azure DevOps), and automated schema migration tooling (Flyway, Liquibase, Redgate).
  • Lead database change management and apply schema migrations safely across environments (development, QA, staging, production) with rollback and migration testing strategies.
  • Plan and execute data migration and consolidation activities for system upgrades, platform migrations, or application decommissioning while preserving data integrity and historical context.
  • Implement and manage backup, restore and disaster recovery processes, including point-in-time recovery, automated backups, and tested restore procedures to meet RTO/RPO objectives.
  • Configure and monitor replication, log shipping, clustering or high-availability technologies (Always On, Mirroring, Replication) to achieve redundancy and minimal downtime.
  • Collaborate with application developers to optimize ORM-generated SQL (Entity Framework, Hibernate) and advise on query patterns, parameterization and connection pooling best practices.
  • Monitor and tune database server configuration parameters, memory settings, tempdb (or equivalent) sizing and storage architecture to improve stability and performance.
  • Develop and execute unit, integration and performance tests for stored procedures, triggers and data transformation logic; participate in code reviews focused on data correctness and performance.
  • Implement security best practices: least-privilege access, role-based access control, encryption at rest/in transit, auditing and compliance-driven data protection.
  • Troubleshoot production incidents, perform root-cause analysis on data-related outages, apply hotfixes or mitigations and create post-incident remediation plans.
  • Partner with BI and analytics teams to design and deliver star/snowflake schemas, materialized views and aggregations for reporting, dashboards and self-service analytics.
  • Build automated monitoring, alerting and observability for database health using tools such as Datadog, New Relic, Prometheus, SQL Sentry or native cloud monitoring.
  • Evaluate and recommend storage, indexing and caching strategies (Redis, in-memory tables, materialized views) to reduce query latency and improve end-user experience.
  • Support adoption of cloud-native database services (AWS RDS/Aurora, Azure SQL Database, Google Cloud SQL, Amazon Redshift) and implement infrastructure-as-code for reproducible deployments.
  • Provide technical mentoring and guidance to junior developers and DBAs on SQL best practices, performance tuning, and stable deployment patterns.
  • Maintain comprehensive technical documentation including schema diagrams, runbooks, data dictionaries and migration plans to support maintainability and onboarding.

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.
  • Assist in vendor evaluations and POC testing for new database, caching or ETL technologies.
  • Provide estimates for database-related tasks during planning and help prioritize technical debt and refactoring work.
  • Help design and enforce data quality rules, validation checks and reconciliation processes for ETL pipelines.
  • Contribute to security reviews, compliance audits and data governance initiatives.
  • Create and maintain automated scripts for routine maintenance tasks (index rebuilds, statistics updates, consistency checks).
  • Participate in capacity planning, storage forecasting and cost optimization efforts for cloud and on-premises data infrastructure.

Required Skills & Competencies

Hard Skills (Technical)

  • Expert SQL development (ANSI SQL) and advanced query optimization skills including experience with execution plans and index tuning.
  • Proficiency with procedural SQL languages: T-SQL (Microsoft SQL Server), PL/SQL (Oracle) or equivalent dialects.
  • Experience designing and implementing ETL processes with SSIS, Talend, Informatica, Azure Data Factory or custom Python-based pipelines.
  • Strong relational database design and data modeling skills (3NF, denormalization, star/snowflake schemas) and familiarity with data warehousing concepts.
  • Performance tuning experience: indexing strategies, partitioning, query refactoring, statistics maintenance and cache utilization.
  • Familiarity with cloud relational database platforms (AWS RDS/Aurora, Azure SQL Database, Google Cloud SQL, Amazon Redshift) and migration strategies.
  • Hands-on experience with backup/recovery strategies, high availability, replication, failover clusters and disaster recovery planning.
  • Experience with NoSQL/document stores (MongoDB, DynamoDB) or key-value caches (Redis) for hybrid storage patterns.
  • Proficiency in scripting and automation (Python, Bash, PowerShell) to create maintenance scripts, ETL tasks and deployment automation.
  • Familiar with database CI/CD, schema migration tools (Flyway, Liquibase) and version control (Git).
  • Knowledge of monitoring and observability tooling for databases (Prometheus, Datadog, New Relic, SQL Sentry) and proactive alerting.
  • Strong understanding of security practices: encryption, masking, role-based access controls, auditing and compliance (PCI, HIPAA, GDPR where applicable).
  • Experience with data integration, API-based data flows and stream processing (Kafka, Logstash) is a plus.
  • Comfortable working with ORMs (Entity Framework, Hibernate) and optimizing generated SQL when necessary.

Soft Skills

  • Excellent analytical and problem-solving skills with a data-driven mindset.
  • Clear and concise communication; able to explain technical database concepts to non-technical stakeholders.
  • Strong collaboration skills; experience working in cross-functional teams with developers, QA, product owners and analysts.
  • Attention to detail and rigor in testing, code reviews and documentation.
  • Ability to prioritize tasks and manage time effectively in a fast-paced, delivery-focused environment.
  • Proactive ownership mentality and accountability for production systems and SLAs.
  • Mentoring and knowledge-sharing orientation to uplift junior team members and promote best practices.
  • Adaptability to changing business requirements and evolving technology stacks.
  • Customer-centric approach when supporting internal teams and external stakeholders.
  • Strong organizational skills and the ability to maintain clear runbooks and operational playbooks.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or a related technical field.

Preferred Education:

  • Master's degree in Computer Science, Data Engineering or equivalent advanced technical education.
  • Professional certifications such as Microsoft Certified: Azure Database Administrator, AWS Certified Database – Specialty, Oracle PL/SQL Developer, or vendor-specific certifications are a plus.

Relevant Fields of Study:

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

Experience Requirements

Typical Experience Range:

  • 2–7 years of hands-on experience building and maintaining relational databases and writing production-grade SQL and procedural code.

Preferred:

  • 5+ years of progressive experience in database development, performance tuning, ETL, and working with cloud database platforms.
  • Demonstrated track record of improving database performance, reducing costs, and delivering reliable data services in production environments.
  • Prior experience in regulated industries or large-scale data platforms is advantageous.
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