2 months ago
Remote, GermanySenior
Responsibilities
- Plan and lead end-to-end enterprise data migration engagements, from source assessment and strategy through production cutover and post-engagement follow-up.
- Design and operate CDC and streaming pipelines for zero- and near-zero-downtime migrations using Kafka, Debezium, connectors, and cloud-native replication services.
- Analyze Cassandra, Cosmos DB, DocumentDB, and other distributed NoSQL platforms to address data modeling, partitioning, consistency, compatibility, economics, and failure-mode risks.
- Collaborate directly with enterprise architects, DBAs, platform teams, executives, Solutions Architects, Engagement Managers, and account teams.
- Scope migration opportunities, shape statements of work and estimation models, identify additional services opportunities, and provide migration expertise to Sales and Professional Services.
- Build AI-assisted migration tooling for estate assessment, schema and data-model conversion, query and code translation, and large-scale validation.
- Create migration playbooks, reference architectures, estimation models, tooling improvements, and enablement for the broader team.
- Partner with Product and Engineering to inform MongoDB's product and migration-tooling roadmap.
Requirements
- A degree in Computer Science or a similar technical field.
- At least 5 years of experience in software engineering, data engineering, or consulting delivery focused on production-scale data platforms and data movement.
- Hands-on experience with Apache Cassandra, Azure Cosmos DB, Amazon DocumentDB, or another distributed NoSQL platform, including data models, consistency, partitioning, and failure modes.
- Real-world CDC and streaming-pipeline experience with Kafka or Confluent Platform, connectors, Debezium or equivalent tooling, schema evolution, delivery guarantees, and backfill-plus-tail patterns.
- Solid grounding in Oracle, SQL Server, PostgreSQL, or MySQL and experience extracting data without disrupting business operations.
- Competence in at least one programming language such as Java, Python, Node.js, C#, or Go for pipeline glue, validation harnesses, and tooling.
- Working fluency with AI in real engineering workflows.
- Strong customer interaction, presentation, analytical, diagnostic, problem-solving, and production-cutover skills.
- An entrepreneurial approach and comfort creating processes and frameworks in ambiguous environments.
- Experience building with LLMs, coding agents, migration or replication tooling, Spark or Flink pipelines, dual-write patterns, cloud DMS-class services, data-validation frameworks, or MongoDB is preferred.
- Architecture-depth experience with AWS, Azure, or GCP, competitive platform displacement experience, and fluency in a second relevant European language are preferred.
Benefits
- Remote work arrangement based in Germany.
- Approximately 30% travel in normal circumstances, primarily within EMEA.
- Employee affinity groups, fertility assistance, and generous parental leave.
- Disability accommodations are available during the application and interview process.
Tech Stack
Apache CassandraApache FlinkApache KafkaApache SparkAWSAzureC#GoGoogle CloudGoogle Cloud PlatformJavaMicrosoft SQL ServerMongoDBMySQLNode.jsPostgreSQLPython
Categories
Solutions Engineering
About MongoDB
MongoDB builds the MongoDB document database and the MongoDB Atlas cloud database service for application developers and enterprises. Its business model centers on cloud consumption (Atlas), commercial subscriptions, and support, with tooling for migration, synchronization, and disaster recovery across on‑prem and multi‑cloud environments. Founded in 2007 and headquartered in New York, it is a public company listed on NASDAQ and widely used across industries worldwide.