About the Role

We’re looking for a Staff Data Engineer to define the architecture and long-term evolution of Syndio’s data platform as we scale into AI-driven products.

This role owns the technical direction for how data is structured, standardized, modeled, and activated across the company, with a particular focus on enabling LLM-powered systems and decisioning workflows.

You will design, architect, and build data pipelines that produce the data products powering analytics, product experiences, and Syndio's LLM-powered systems. Your work will shape how data is used across the company and enable the development of Syndio's decision graph and AI capabilities. This includes solving complex challenges such as multi-tenant schema standardization, automated field mapping, retrieval-ready data modeling, and data pipelines for AI evaluation and feedback loops.

You will operate across pipeline architecture, platform design, and cross-functional data strategy, partnering closely with product, data science, and engineering leadership.

Why This Job is Exciting

• Define the data architecture behind AI for Pay Decisions and future decisioning systems
• Build the data foundation that powers LLM-based features, including the pipelines that feed retrieval, context generation, and evaluation workflows
• Own high-leverage problems like automated schema mapping and multi-tenant data standardization
• Establish standards for data contracts, modeling, and pipeline architecture across teams
• Design data governance into the platform through policy tagging, PII handling, and lineage tracking
• Build pipelines that support both batch analytics and the event-driven data flows behind AI workflows
• Shape how data is structured, delivered, and made reliable for stakeholders across Syndio, from analytics and product teams to the teams training and evaluating AI systems

About You

• Deep experience in data engineering, data platform, or distributed systems roles
• Proven track record designing and scaling data pipelines across teams or organizations
• Experience solving ambiguous, high-impact platform problems and building systems widely adopted across teams
• Strong ability to operate at both architectural and hands-on levels
• Cross-functional leadership and ability to influence technical direction

Required Areas of Deep Expertise

• Data modeling and schema design
• Pipeline architecture and orchestration
• Data warehouse and storage systems

Technical Experience

• Strong proficiency in Python and SQL
• Experience with data patterns for AI/LLM systems: retrieval-ready data modeling, vector storage, embedding pipelines, and evaluation datasets
• Cloud platforms: GCP (preferred), AWS, or Azure
• Cloud data warehouses: BigQuery, Snowflake, Redshift, or similar
• Data transformation: dbt or equivalent modern transformation frameworks
• Relational databases: Postgres, MySQL, or similar
• Streaming and CDC ingestion patterns (Datastream, Debezium, Kafka, or similar)
• Data governance and lineage tooling

Nice to Have

• Experience building AI-native data platforms or developer tooling
• Experience with event-driven or streaming architectures
• Background in high-scale systems or large multi-tenant SaaS platforms
• Familiarity with compensation or HR data domains

How we work:

• We believe in starting simple, soon — progress over perfection. We value architectural clarity and execution speed. You’ll be joining a small, ambitious team committed to high trust, low ego collaboration. It’s a dynamic environment where teams embrace ambiguity, adapt quickly to change, and move fast to seize opportunity. As such, we empower engineers to make bold moves and back it up with a culture that supports learning through iteration.
• Applicants must currently reside within commuting distance of Calgary, Alberta, Canada for consideration. Relocation is not currently offered.
  • Kindly note, you must also be eligible to work in Canada legally, as we are NOT able to provide visa support or transfer at this time.

Why you'll love it here:

• 💰 Competitive Compensation. For this role our base salary is targeted at $180-195k CAD. Final offer amounts are determined by factors such as experience and expertise. We take a geo neutral approach to compensation within the US, meaning that we pay based on job function and level, not location. 
• 🏆 Syndio Equity. So you can share in Syndio’s success.
• 🏝 20 days annually. We encourage our team to recharge when they need to, plus paid sick & safe time, compassion leave, and voting leave. 
• 🏦 Pension Contribution
• 📍 Remote-First with opportunities for local meet-ups in Calgary #LI-Remote 

Role Progression:

• By the 3rd Month, you will have a working knowledge of Syndio's data domain and existing pipeline architecture. You'll be making hands-on contributions to the data layer codebase, building familiarity with the systems you'll eventually evolve.
• By your 6th Month, you will take technical ownership of the AI data infrastructure, defining the architectural direction for how data is modeled and served to AI systems. You'll establish company-wide standards for data contracts and pipeline architecture, and lead solutions for our hardest data standardization challenges.
• By 9 months in, you will set the long-term technical direction for Syndio's data platform and AI-driven systems, with a focus on governance, PII handling, and lineage. As the SME, you'll mentor other engineers and break down complex platform initiatives for the team to execute.

The Interview Overview:

Below you'll find an outline of the interview plan for our Staff Data Engineer position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

1. 30 min - Phone call with a member of our Talent Team
2. 45 min - Zoom interview with the Hiring Manager
3. Technical Evaluation - Take-home
4. 1.5 hrs - Meet the Team
5. 30 min - Final Interview

MongoDB is building a world-class team in North America to create tooling that helps customers modernize their applications and migrate their data from legacy relational databases to MongoDB in real-time. As companies modernise legacy workloads and data ecosystems, they are increasingly drawn to the flexibility and scalability of the document model. The tools developed by the Code Generation and Data Migration team are critical in this journey, helping customers with schema modeling, code generation, initial data loads, and continuous data synchronization.

We're looking for a Senior Engineer with a strong background in computer science fundamentals, systems design, experience in the Java ecosystem, streaming systems, and data-intensive applications to join our engineering team. In this role, you will be instrumental in designing, building, and optimizing the underlying data structures, algorithms, and database interactions that power our generative AI platform, code generation and migration tools. This involves crafting sophisticated orchestration layers, robust integration points, and high-performance data systems that seamlessly connect and leverage advanced AI capabilities for code generation and  building a sophisticated data migration suite using a modern technology stack, which includes Java, Spring Boot, Kafka, Debezium, and React.You will work on critical components that ensure the scalability, efficiency, and reliability of our services, collaborating closely with AI researchers, product management and other engineers to design and implement cutting-edge products that solve complex customer challenges.

This role will be based out of North America in the PST and MST zones only.

The ideal candidate for this role will have

• 2+ years of  engineering experience in backend systems, distributed systems, or core platform development
• Experience in one or several of Java, Rust, C/C++, and/or Python, with a strong understanding of systems-level programming, memory management, and performance tuning
• Experience with streaming data platforms such as Apache Kafka and Change Data Capture (CDC) tools like Debezium
• Experience with relational data modeling and hands-on experience with at least one SQL database (Postgres, MySQL, etc)
• Exposure to client-side technologies such as JavaScript and React is a plus
• Good understanding of algorithms, data structures and their time and space complexity
• Curiosity, a positive attitude, and a drive to continue learning
• Excellent verbal and written communication skills

Nice to Have

• Familiarity with cloud-native distributed systems (e.g., Kubernetes)
• Experience with NoSQL databases and understanding of their trade-offs is great, but not required. We'll teach you NoSQL
• Contributions to relevant open-source projects

Position Expectations

• Contribute high-quality, well-tested backend code to the data migration engine and core components of our generative AI orchestration platform
• Collaborate effectively with Product Management, AI researchers and machine learning engineers and designers to build and deliver on the product roadmap
• Work to develop robust and efficient backend services that orchestrate AI functionalities
• Identify and address performance bottlenecks and architectural challenges in our systems, particularly within data flow and orchestration
• Participate actively in code reviews to enforce best practices and patterns
• Help troubleshoot and resolve complex technical issues in our distributed systems
• Give and solicit feedback on technical design documents and pull requests
• Perform tasks related to process such as CI/CD, quality, testing, etc 

Success Measures

Within the first three months, you will have:

• Familiarize yourself with the MongoDB database and aggregation language
• Familiarize yourself with the backend tech stack including Java, Spring Boot, and Kafka
• Set up software development infrastructure (tech stack, build tools, etc) to enable development using the relevant tech stacks
• Started collaborating with your peers and contributed to code reviews

Within six months, you will have:

• Familiarised yourself with the rest of our the application modernization tool stack
• Delivered at least one large scale feature that spans the entire tech stack
• Reviewed and contributed to scope and technical design documents

Within 12 months, you will have:

• Become a key contributor to our backend stack, capable of taking on complex features independently
• Helped recruit and interview new members of the team
• Collaborated effectively with other teams at MongoDB on cross-functional projects

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

REQ ID: 425547