Lead Database Engineer

Work Schedule

Environmental Conditions

Job Description

Summarized Purpose:

We are seeking a Lead Database Engineer to design build optimize and support AWS-based data lake data warehouse and database platforms. This role will lead database architecture performance tuning data quality lineage source-to-target mapping production support and technical delivery across PostgreSQL Redshift Athena DynamoDB SQL Server and related AWS services.

Education/Experience:

• Bachelors degree or equivalent experience and relevant formal academic/vocational qualification.
• Previous roles showcasing 7 years of database engineering data architecture AWS data platform SQL development performance tuning and production support experience or an equivalent blend of education training and experience.

Major Job Responsibilities:

• Design build and maintain AWS-based data lake and warehouse architecture using S3 Redshift DynamoDB RDS Athena and related cloud data services.
• Optimize PostgreSQL Redshift Athena DynamoDB SQL Server and SQL-based workloads for performance reliability scalability and cost.
• Lead data integrations ETL processes database operations and source-to-target mapping based on stakeholder and collaborator requirements.
• Maintain and improve existing integrations while adding new EMR clinical operational and enterprise data integrations.
• Implement data quality frameworks automated validation reconciliation monitoring and alerting to ensure accurate warehouse and lakehouse loads.
• Normalize EMR claims clinical operational and flat-file data into data warehouse analytical and downstream reporting structures.
• Develop and maintain mapping tables data dictionaries source-to-target mappings metadata lineage and technical documentation for analysts and downstream systems.
• Link and transform patient activity operational and business data into standardized outputs for analytics and reporting.
• Implement backup recovery replication retention and operational readiness requirements for production databases and data platforms.
• Maintain database documentation describing data elements transformations lineage interfaces ownership and usage patterns.
• Develop new data architecture and database processes to improve performance using AWS analytical services and lakehouse architecture patterns.
• Use Python PySpark SQL and automation scripts to support data processing validation migration and operational workflows.
• Ensure database security and compliance with HIPAA GDPR access control auditability encryption and data governance requirements.
• Manage production operations including recurring reports pipeline support issue triage change management and release coordination.
• Communicate with stakeholders mentor engineers perform code reviews and maintain strong relationships with cross-functional collaborators.

Knowledge Skills and Abilities:

• Strong understanding of data lake data warehouse and lakehouse architecture patterns on AWS.
• Client-focused approach with strong interpersonal documentation communication and technical leadership skills.
• Ability to multitask prioritize manage production issues and maintain attention to detail in complex data environments.
• Strong logical analytical thinking root-cause analysis and problem-solving capabilities.
• Proficiency in Python PySpark SQL scripting Shell scripting and automation for database and data platform operations.
• Expert-level SQL and relational database design including schema design normalization dimensional modeling and query optimization.
• Deep knowledge of PostgreSQL performance tuning indexing partitioning stored procedures/functions replication backup and recovery.
• Strong hands-on experience with PostgreSQL Redshift SQL Server Athena DynamoDB RDS S3 and AWS data services.
• Strong performance tuning experience across PostgreSQL Redshift Athena DynamoDB SQL Server and SQL-based workloads.
• Familiarity with server environments database connectivity data movement security governance and compliance standards.
• Experience with validated systems healthcare data EMR integrations clinical trial data and regulated production environments preferred.
• Project management Agile delivery GitHub workflows Jira tracking documentation code review and leadership experience.

Must Have Skills:

• Expert-level SQL expertise and relational database design experience.
• Advanced SQL Server experience including database development optimization stored procedures SSIS SSRS and operational support.
• Strong hands-on PostgreSQL and Redshift experience including administration tuning data modeling backup recovery and production operations.
• Experience building AWS data lake data warehouse and cloud BI solutions using S3 Redshift Athena DynamoDB RDS and related services.
• Experience with data architecture scalable data processing frameworks ETL patterns lakehouse design and production-grade data pipelines.
• Data modeling database design source-to-target mapping data lineage data dictionary and technical documentation experience.
• Strong problem-solving analytical troubleshooting production support and incident management skills.
• Excellent documentation communication stakeholder management and cross-functional collaboration abilities.
• Performance tuning and query optimization across PostgreSQL Redshift Athena SQL Server and large SQL workloads.
• Leadership mentoring code review database standards and technical decision-making capabilities.
• Jira GitHub Agile methodology CI/CD awareness release management and delivery tracking experience.
• Experience implementing data quality frameworks pipeline monitoring alerting reconciliation and production support processes.

Good to Have Skills:

• Experience with MySQL Oracle Aurora PostgreSQL RDS and additional relational or NoSQL database platforms.
• Scripting and automation skills using Python Shell SQL automation or AWS SDKs.
• Validated system experience and regulated SDLC documentation practices.
• Familiarity with Tableau Power BI or reporting and BI consumption patterns is helpful.
• Familiarity with Databricks Snowflake Glue Lake Formation Step Functions Lambda or modern lakehouse tooling.
• Experience with machine learning NLP LLMs AI-assisted documentation mapping automation vector databases embeddings or LLM-enabled data quality is an advantage.
• Healthcare Electronic Medical Records claims data clinical trial data HIPAA GDPR and patient data domain experience.

Working Hours:

• India: 05:30 PM to 02:30 AM IST
• Philippines: 08:00 PM to 05:00 AM PHT