Movimentum is hiring a Senior Data Engineer to own the reliability, security, and evolution of our core data platforms. This role sits at the intersection of data engineering, platform reliability, and data security, designing and operating the data systems that power our analytics, reporting, decision engines, and regulatory workflows.

What You'll Do

Design and operate scalable batch and streaming data pipelines
Own data ingestion, transformation, and serving layers across systems
Build reliable data platforms used by analytics, product, and AI teams
Ensure data quality, freshness, and correctness at scale
Design secure access patterns for sensitive financial data
Implement encryption, access controls, and audit-ready data workflows
Partner with product, risk, compliance, and InfoSec teams
Debug data failures, delays, and inconsistencies in production
Take ownership during data incidents and reliability issues

What We're Looking For

Bachelor’s/Master’s degree in Computer Science, Engineering, Data Science, or related field
5+ years building production-grade data engineering systems
Strong Python and SQL fundamentals
Experience designing and maintaining ETL / ELT pipelines
Experience with cloud-native data platforms (AWS preferred)
Strong understanding of data modelling and warehouse design
Experience operating relational and NoSQL databases in production
Solid grasp of data security fundamentals (IAM, PAM, encryption, access control)
Ability to reason about performance, cost, and reliability trade-offs

Nice to Have

Experience with financial, trading, or wealth management data
Exposure to streaming or event-driven data systems
Experience with data governance, lineage, or cataloging
Familiarity with compliance-driven environments (SEBI, SOC, ISO)
Experience working closely with InfoSec or risk teams

Technical Stack

Python, SQL, AWS
ETL/ELT
Relational Databases, NoSQL Databases

Team & Environment

You will partner with product, risk, compliance, and InfoSec teams. Our engineering culture values systems thinking, strong ownership of data correctness and security, a bias toward reliability over cleverness, comfort operating in regulated environments, and engineers who debug production issues end-to-end.