Manager of SQL Engineering leading global SQL teams across onshore, nearshore, and offshore. Overseeing enterprise data platforms including SQL Server, PostgreSQL, MongoDB, and Amazon Document DB.
Responsibilities
Lead, mentor, and develop a distributed SQL engineering organization across onshore, nearshore, and offshore talent pools.
Oversee the design, optimization, and maintenance of SQL Server, Aurora/Postgres, MongoDB, and DocumentDB environments.
Own the workflows involving eCommerce rate loading, data ingestion, and large-scale data transformations.
Ensure data models, schemas, and architectures support scalable, reliable, and performant systems.
Guide data transformation strategies across databases and ensure consistency, and data quality across platforms.
Drive engineering best practices including query optimization, indexing strategies, schema versioning, monitoring, and observability.
Manage data promotion processes across development, QA, staging, and production environments.
Ensure systems meet operational excellence standards including availability, performance, backup/recovery, and security.
Partner with application development teams to optimize queries, APIs, and data access patterns.
Collaborate with CloudOps/DevOps teams to support automation, CI/CD, and environment provisioning for database changes.
Coordinate with global vendors and offshore partners to ensure delivery quality and consistency.
Lead production incident response for data-related issues, including root-cause analysis and continuous improvement actions.
Build a strong culture of ownership, quality, documentation excellence, and continuous learning.
Provide coaching, performance management, and career development for SQL engineers and analysts.
Requirements
8+ years of experience in database engineering, data engineering, or data platform roles.
3+ years leading global, distributed technical teams (onshore/nearshore/offshore).
Deep hands-on experience with SQL Server, PostgreSQL/Aurora, MongoDB, and Document DB.
Strong background in database design, normalization/denormalization, schema modeling, and performance tuning.
Experience building and managing data transformation workflows and relational-to-NoSQL data pipelines.
Proven ability to manage database changes and data promotion across multiple environments.
Strong understanding of production operations, including backups, monitoring, optimization, and troubleshooting.
Experience with high-volume transactional or eCommerce systems is strongly preferred.
Knowledge of cloud environments (especially AWS), ETL/ELT tooling, and CI/CD processes for database deployments.
Experience with Gen AI solutions (e.g., AI-assisted SQL optimization, code generation, documentation automation, or data quality intelligence) is a significant plus.
Strong communication skills with the ability to influence both technical and non-technical stakeholders.
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