Senior Consulting Engineer

The team MongoDB's Application Modernization Platform (AMP) organization is the front door of our modernization business. In our Data Migration practice we move production data - safely, repeatably, at enterprise scale - from relational estates (Oracle, SQL Server, PostgreSQL, MySQL) and from NoSQL platforms (Apache Cassandra, Azure Cosmos DB, Amazon DocumentDB) onto MongoDB. We do this both as standalone migration programmes and as the data workstream inside larger application-modernization engagements, using MongoDB's own tooling - Relational Migrator, Cluster-to-Cluster Sync, Atlas Stream Processing - alongside the open-source and cloud-native pipeline ecosystem.

Our mission is to help our customers be successful by leading end-to-end their journey to MongoDB. In an era where AI agents handle routine migration mechanics - such as workload assessments, schema and query translations, and large-scale validation - our consultants focus on the high-judgment decisions that directly mitigate risk. Joining us now means helping draft the playbooks while they are actively being defined. We are seeking builders who prefer creating new frameworks over following legacy instructions. This role will be based remotely in Germany. Position expectations Delivery Plan and lead the technical delivery of data migration engagements end to end: source estate assessment, migration strategy and wave planning, schema and data-model transformation, pipeline build, validation, and production cutover with minimal downtime Design and operate change data capture (CDC) pipelines for zero and near-zero-downtime migrations - using Kafka and the connector ecosystem, Debezium and comparable log-based CDC tooling, and cloud-native replication services Bring genuine platform depth on the estates our customers are leaving: Cassandra data modeling and anti-patterns, Cosmos DB (Core and Mongo API) partitioning and RU economics, DocumentDB's compatibility surface - and use it to de-risk what the customer cannot see coming Work shoulder to shoulder with enterprise customers - architects, DBAs, platform teams and executives - from whiteboard to war room Own the full consulting lifecycle for your engagements, from planning and agenda-setting through post-engagement follow-up, surfacing risks and further opportunities back to Sales and Professional Services Pre-sales and growth Partner with Solutions Architects, Engagement Managers and account teams to scope and size migration opportunities, shape statements of work and estimation models, and give sales well-founded confidence in what is achievable and what it will take Cultivate your reputation as a migrations SME and trusted advisor, internally and in the market, and positively influence your own utilization through proactive customer engagement Identify services opportunities in our customers, new workloads or estates to be migrated or product improvements the customer could benefit from Building the practice Build and harden the AI tooling that makes migrations faster and safer: agents for automated estate assessment, schema and data-model conversion, query and code translation, and large-scale data validation - and fold what works into the standard delivery methodology Turn field experience into reusable assets: migration playbooks, reference architectures, estimation models, tooling improvements and enablement for the wider team Partner with Product and Engineering to bring field reality into MongoDB's product and migration-tooling roadmap Candidate profile Excellent analytical, diagnostic and problem-solving skills, and the composure to apply them during a production cutover Degree in Computer Science or a similar technical field, and a technology-first mindset that lets you build credibility with some of the smartest technologists in the world 5+ years in software engineering, data engineering, or consulting delivery roles centred on data platforms and data movement at production scale Hands-on experience with at least one of: Apache Cassandra, Azure Cosmos DB, Amazon DocumentDB, or another distributed NoSQL platform - deep enough to reason about data models, consistency, partitioning and failure modes, not just operate one Real-world CDC and streaming-pipeline experience: Kafka or Confluent Platform, connectors, Debezium or equivalent, schema evolution, exactly-once versus at-least-once trade-offs, backfill-plus-tail patterns Solid grounding in relational databases (Oracle, SQL Server, PostgreSQL or MySQL) and in getting data out of them without breaking the business Competence in at least one programming language (Java, Python, Node.js, C#, Go or similar) - enough to build pipeline glue, validation harnesses and tooling, not only to configure products Working fluency with AI in real engineering workflows Excellent customer interaction and presentation skills: you can explain a partitioning strategy to a DBA at 10:00 and a migration risk profile to a Senior Leadership at 11:00, and both leave more confident than they arrived An entrepreneurial bias. You see the gaps and what is missing. You are comfortable operating where the process does not exist yet, and you would rather ship a rough first version and iterate than wait for the shape to be agreed MongoDB expertise is not a requirement. We will teach you MongoDB - that is the part we are world-class at. What we cannot teach is the scar tissue from the platforms and pipelines above. Bring that.

Nice to have

Experience building with LLMs beyond personal productivity: you use LLMs and coding agents as part of how you build and deliver today Migration or replication tooling experience: Spark or Flink-based pipelines, dual-write patterns, cloud DMS-class services, data-validation frameworks One or more cloud platforms (AWS, Azure, GCP) at architecture depth Experience on the vendor or consulting side of competitive platform displacements Practical experience with MongoDB Fluency in a second European language relevant t