DIGITAL MEDIA SOLUTIONS LLC - Manager, Data Engineer

DIGITAL MEDIA SOLUTIONS LLC - Manager, Data Engineer





















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Manager, Data Engineer






DIGITAL MEDIA SOLUTIONS LLC





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Manager, Data Engineer




Fully Remote









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Description
Location: US-Remote (AL,AZ,CA,CO,CT,DC,FL,GA,ID,IL,IN,MA,MD,MI,MO,NC,NH,NJ,NV,NY,OH,PA,RI,TN,TX,UT,VA,WA,WI)Type: Full-Time, Salary, ExemptAbout DMSDigital Media Solutions (DMS) is a performance-driven digital marketing company that connects consumers and brands through data, technology, and proprietary media solutions. Operating in high-volume, transaction-intensive markets, DMS manages multiple revenue streams, variable margins, and complex unit economics across its portfolio of offerings. The company partners closely with clients to deliver measurable outcomes, leveraging analytics, optimization, and disciplined execution in dynamic market conditions.About this RoleWe’re looking for a Manager, Data Engineering to lead the team responsible for the reliability, scalability, and performance of our data infrastructure. You will manage a team of data engineers and be accountable for the platforms and pipelines that power DMS’s data-driven business.This role owns the strategy and execution across high-availability transactional systems (MySQL, PostgreSQL, DynamoDB), ELT/ETL pipelines, Kafka streaming architectures, replication systems, and data warehousing infrastructure. You will partner closely with core engineering, data science, product, and infrastructure teams to ensure safe, scalable, and cost-efficient data movement across the organization.Why Join DMS?At Digital Media Solutions, you’ll work at the core of a high-scale marketing marketplace that processes millions of consumer interactions and signals daily. Your work will directly impact how traffic is evaluated, matched, and monetized—giving you clear visibility into how data drives revenue and performance.In this role, you won’t just report on data—you’ll shape it. You’ll have the opportunity to influence lead quality, improve buyer matching, and optimize campaign outcomes in real time. You’ll work with modern analytics tools and large datasets, gaining hands-on experience in a fast-paced environment where insights quickly turn into action.If you enjoy solving complex problems, working with high-volume data, and seeing the direct impact of your work on business performance, this is an opportunity to make a meaningful impact.
Requirements
What You’ll DoLead, mentor, and grow a team of data engineers and architectsDefine 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 workflowsDrive strategy and reliability for ELT/ETL pipelines and Kafka-based streaming architecturesSet standards for performance optimization, query tuning, indexing, and database scaling across teamsOversee backup, failover, disaster recovery (PITR), and incident response for all production data systemsDrive 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 workPartner cross-functionally with backend, data science, infrastructure, and product teams to align on data platform prioritiesEstablish engineering guardrails, best practices, and documentation to enable team autonomy and quality at scaleLead 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 decisionOwn 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 consumptionOversee 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 throughoutTechnical EnvironmentDatabases: MySQL, PostgreSQL, DynamoDB, Elastic, RedisStreaming: Kafka (CDC, event streaming)Cloud: AWS (RDS, Aurora, DynamoDB)Data Warehouse: AWS Redshift, Snowflake, Databricks Monitoring: Datadog, CloudWatchTooling: Go, Python, BashData Movement: ELT / ETL pipelinesWhat We’re Looking For8+ years of data or database engineering experience, with 2+ years in an engineering management roleDeep hands-on experience with MySQL and/or PostgreSQL in high-availability production environmentsProven track record leading and developing teams of engineers in fast-paced, data-intensive environmentsStrong expertise in binlog/logical replication and integrating OLTP systems with KafkaExperience designing and supporting ELT/ETL pipelines safely at scaleDeep understanding of ACID principles, transaction isolation, and database internalsExperience with AWS-managed database services (RDS, Aurora, DynamoDB) and infrastructure cost managementExperience evaluating or migrating data warehouse platforms (Redshift, Snowflake, Databricks, or similar)Experience designing or redesigning dimensional or analytical data models for large-scale warehouse environmentsOLTP vs OLAP workload separation and architectural decision-making experienceAbility to balance performance, cost, and compliance at an organizational levelStrong communication skills with the ability to translate technical complexity for non-technical stakeholdersNice to HaveExperience with CDC implementation and large-scale database migrationsInfrastructure-as-code experience (Terraform)Background in high-volume, transaction-intensive production environmentsPrior experience building or scaling a data engineering function from the ground upExpectations at Manager LevelOwns team health, technical direction, and delivery outcomes for the data engineering functionDesigns and communicates safe, scalable replication and streaming architectures to senior leadershipProtects transactional systems from downstream risk at an organizational levelAnticipates scaling and cost challenges and proactively drives solutions across the teamEstablishes guardrails, engineering standards, and a culture of ownership across data engineering teamsCOMPENSATION: The anticipated annual base salary for this position is $180,000–$200,000. Actual compensation may vary based on work experience, education, and skill level.
Salary Description
$180,000-200,000 annually


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