Manager, Data Engineer

Role Overview

• Lead, mentor, and grow a team of data engineers and architects
• Define and execute the technical roadmap for production database systems (MySQL, PostgreSQL, DynamoDB, Elastic)
• Own the architecture and governance of binlog replication, logical replication, and CDC workflows
• Drive strategy and reliability for ELT/ETL pipelines and Kafka-based streaming architectures
• Set standards for performance optimization, query tuning, indexing, and database scaling across teams
• Oversee backup, failover, disaster recovery (PITR), and incident response for all production data systems
• Drive cost efficiency, infrastructure optimization, and monitoring across cloud-managed data services (AWS RDS, Aurora, DynamoDB)
• Champion data integrity, security, and compliance standards across all data engineering work
• Partner cross-functionally with backend, data science, infrastructure, and product teams to align on data platform priorities
• Establish engineering guardrails, best practices, and documentation to enable team autonomy and quality at scale
• Lead the evaluation and selection of next-generation data warehousing technology (Snowflake, Databricks, AWS Redshift Serverless) — assessing performance, cost, ecosystem fit, and migration complexity to inform a platform decision
• Own the design of an upgraded data model for the warehouse in partnership with data engineers and architects, establishing standards for schema design, partitioning, access patterns, and downstream consumption
• Oversee the end-to-end migration from the current Redshift warehouse — planning the phased approach, managing cutover risk, and ensuring continuity of downstream reporting and analytics throughout

Requirements

• 8+ years of data or database engineering experience, with 2+ years in an engineering management role
• Deep hands-on experience with MySQL and/or PostgreSQL in high-availability production environments
• Proven track record leading and developing teams of engineers in fast-paced, data-intensive environments
• Strong expertise in binlog/logical replication and integrating OLTP systems with Kafka
• Experience designing and supporting ELT/ETL pipelines safely at scale
• Deep understanding of ACID principles, transaction isolation, and database internals
• Experience with AWS-managed database services (RDS, Aurora, DynamoDB) and infrastructure cost management
• Experience evaluating or migrating data warehouse platforms (Redshift, Snowflake, Databricks, or similar)
• Experience designing or redesigning dimensional or analytical data models for large-scale warehouse environments
• OLTP vs OLAP workload separation and architectural decision-making experience
• Ability to balance performance, cost, and compliance at an organizational level
• Strong communication skills with the ability to translate technical complexity for non-technical stakeholders.

Tech Stack

• Amazon Redshift
• AWS
• Cloud
• DynamoDB
• ETL
• Kafka
• MySQL
• Postgres