Senior Database Engineer / Data Platform Engineer - Contract

This role requires a strong focus on production reliability, data integrity, performance, security, and risk management. The candidate will be responsible for executing complex data changes safely, optimizing database performance, supporting data platform architecture, and collaborating with engineering, analytics, and product teams to deliver reliable and scalable data solutions in a healthcare product environment., * Design, administer, and optimize databases including PostgreSQL, Oracle, and NoSQL/non-relational systems (e.g., MongoDB, Cassandra, DynamoDB, Redis)

• Write, tune, and review complex SQL queries, stored procedures, functions, and triggers
• Plan and execute large-scale data changes in production (bulk updates, migrations, backfills, schema changes) with minimal downtime and risk
• Build rollback, validation, and backup strategies for every production data change
• Work with datasets in the tens of millions of records and beyond, ensuring performance and scalability
• Design and support data lake architectures and integrate them with analytics and reporting pipelines
• Partner with analytics, engineering, and product teams to enable reliable, high-quality data for decision-making
• Monitor database health, troubleshoot performance issues, and manage indexing, partitioning, and capacity planning
• Implement data security, access control, and compliance best practices
• Evaluate and recommend new database technologies, tools, and approaches

• Strong, hands-on experience with PostgreSQL and Oracle
• Working experience with non-relational databases and knowing when to use them over RDBMS
• Expert-level SQL skills, including query optimization, execution plan analysis, and performance tuning
• Proven track record of making large data changes in production safely, such as batching, online migrations, and zero or low downtime approaches
• Experience handling large-scale data (tens of millions of rows or more)
• Solid understanding of data lakes, data warehousing concepts, and the role of data analytics in business decisions
• Knowledge of backup, recovery, replication, and high-availability strategies
• Strong problem-solving skills and attention to detail, especially in high-stakes production environments

Preferred Qualifications

• Experience with CI/CD and version control for database changes (Liquibase, Flyway)
• Familiarity with ETL/ELT tools and orchestration (Airflow, dbt, Spark, Kafka)
• Scripting skills (Python, Bash, or PL/SQL) for automation
• Experience with cloud data platforms (AWS, Azure, or GCP) and services such as S3, Redshift, BigQuery, Snowflake, or Databricks
• Exposure to BI tools (Tableau, Power BI, Looker)
• Certifications in Oracle, PostgreSQL, or cloud data platforms

Key Competencies

• Technical Expertise: Strong database engineering, SQL optimization, and data platform knowledge.
• Production Risk Management: Careful planning, testing, validation, rollback readiness, and controlled execution of production changes.
• Problem Solving: Ability to diagnose complex database issues and deliver sustainable solutions.
• Ownership and Accountability: Responsibility for database performance, availability, reliability, and data quality.
• Collaboration: Effective communication with engineering, analytics, product, infrastructure, and business stakeholders.
• Continuous Improvement: Commitment to evaluating new technologies, automating repetitive work, and improving operational practices.

Expected Outcomes

• Reliable, secure, and high-performing database platforms.
• Safe execution of large-scale production data changes with minimal disruption.
• Improved SQL performance, database scalability, and operational efficiency.
• Strong data integrity, validation, recovery, and change management practices.
• Scalable data platforms that support analytics, reporting, and evolving business needs.