Manager, Data Engineer

Job not on LinkedIn

🕒 3 days ago

🏈 Alabama, Arizona, +25 more states – Remote

🏈 Alabama – Remote 🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🐊 Florida – Remote 🥔 Idaho – Remote 🌽 Illinois – Remote 🎰 Nevada – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote 🏰 Missouri – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ⚔️ Virginia – Remote ☕ Washington – Remote 🧀 Wisconsin – Remote

💵 $180k - $200k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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Digital Media Solutions

WebsiteLinkedInAll Job Openings

201 - 500 employees

🛍️ eCommerce

💸 Finance

💰 Post-IPO Equity on 2023-03

Advertising • eCommerce • Finance

Digital Media Solutions is a company that specializes in connecting high-intent consumers with advertisers across a variety of verticals including insurance (auto, home, health), education, consumer finance, and ecommerce. Established in 2012, DMS focuses on delivering superior service and innovative digital performance advertising solutions. The company's approach is centered around compliance, leveraging industry expertise, and prioritizing customer needs to ensure brand safety and effective advertising. DMS helps advertisers achieve a superior return on ad spend while assisting consumers in making informed purchasing decisions. Recently, DMS transitioned ownership of its core business assets and subsidiaries to existing lenders and Imon Media LTD as part of a court-supervised sale process.

📋 Description

• 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.