[Hiring] Database Engineer @Modus Create

Role Description

You won't be building from the sidelines. As a Modus Database Engineer embedded in our Modus Data & ML practice, you operate as a forward deployed engineer — right at the frontier of enterprise data transformation. You'll work directly with clients to accelerate pre-sales opportunities, collaborating with Sellers, to turn data challenges into production-grade solutions.

Our team drives database migration, modernization, and platform engineering for some of the largest organizations in the world — helping them:

• Re-host on AWS EC2
• Re-platform to RDS
• Re-factor to Aurora PostgreSQL/MySQL/NoSQL
• Migrate Oracle/Exadata workloads to ODB@AWS

You'll be in the room (or the call) where it happens, turning ambiguity into architectures and architectures into outcomes. This isn't a role for people who want to sit back and review tickets. You'll:

• Lead Executive Conversations, drive proof-of-concepts, run technical workshops, and build reusable IP that multiplies impact across customers, market segments, and technology domains.
• Thrive on complexity, love building scalable patterns, and want your work to directly shape enterprise deals and client outcomes.

Qualifications

• Hands-on experience with database migration and modernization projects — ideally involving AWS data services (RDS, Aurora, DynamoDB, Redshift, DMS, SCT).
• Deep proficiency in one or more relational database platforms: PostgreSQL, MySQL, Oracle, or SQL Server — including schema design, query optimization, and replication.
• Proven ability to architect and implement data pipelines, ETL/ELT workflows, and integration patterns at scale.
• Experience with Oracle or Exadata migrations — including assessment, schema conversion, and cutover planning — is strongly valued.
• Solid understanding of AWS infrastructure fundamentals: EC2, VPC, IAM, S3, and compute/storage considerations for database workloads.
• Comfort operating in pre-sales and client-facing contexts — you can translate technical depth into business language without losing the signal.
• Ability to lead proof-of-concept engagements end-to-end: scope, build, validate, and present results to senior stakeholders.
• Strong software engineering fundamentals — you write clean, maintainable code and understand how data engineering fits into broader application architectures.
• Experience working in distributed, async-first teams; you don't need to be in the same timezone to drive outcomes.

Requirements

• Experience with NoSQL platforms: DynamoDB, MongoDB, Cassandra, or similar — especially in migration or modernization contexts.
• Familiarity with GenAI-assisted data migration tooling, LLM-powered schema translation, or AI-driven data quality workflows.
• AWS certifications (Database Specialty, Solutions Architect, or Data Analytics).
• Experience with data lakehouse architectures, Apache Iceberg, Glue, or Athena.
• Background in consulting, professional services, or solutions engineering — you know how to run a room.
• Contributions to open-source data tooling, migration frameworks, or reusable architectural patterns.

Benefits

• Being the technical voice in the room — not just a builder in the back, but a strategic force in enterprise deals.
• Working at the intersection of data engineering, cloud infrastructure, and generative AI on problems that actually matter at scale.
• Building reusable IP that outlives individual engagements and shapes how entire market segments modernize their data platforms.
• Collaborating with Fortune 500 clients, and a globally distributed team of sharp, low-ego engineers.
• The autonomy to define solutions, the support to deliver them, and the recognition when they land.