Manager, Data Engineer

Emploi pas sur LinkedIn

🕒 il y a 1 mois

🏈 Alabama, Arizona, +25 états de plus – Distant

🏈 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

💵 $200 000 - $230 000 / an

⏰ Temps Plein

🟠 Senior

🔴 Expert

🚰 Ingénieur Data

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Digital Media Solutions

Site WebLinkedInTous les Emplois

201 - 500 employés

🛡️ Assurance

💼 Conseil

📦 Logistique

💰 Post-IPO Equity en 2023-03

Insurance • Consulting • Logistics

Digital Media Solutions est une entreprise spécialisée dans la mise en relation des consommateurs à forte intention d'achat avec des annonceurs dans divers secteurs, notamment l'assurance (auto, habitation, santé), l'éducation, la finance de consommation et le commerce électronique. Fondée en 2012, DMS se concentre sur la prestation d'un service supérieur et des solutions publicitaires numériques innovantes axées sur la performance. L'approche de l'entreprise repose sur la conformité, l'exploitation de l'expertise sectorielle et la priorité aux besoins des clients pour garantir la sécurité des marques et une publicité efficace. DMS aide les annonceurs à obtenir un meilleur retour sur investissement publicitaire tout en aidant les consommateurs à prendre des décisions d'achat éclairées. Récemment, DMS a transféré la propriété de ses principaux actifs et filiales commerciales aux prêteurs existants et à Imon Media LTD dans le cadre d'un processus de vente supervisé par le tribunal.

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

🎯 Exigences

• 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.