Senior Data Engineer

About the Role

We are hiring a Senior Data Engineer to own the reliability, security, and evolution of Neos core data platforms.

This role sits at the intersection of data engineering, platform reliability, and data security.

You will design and operate data systems that power analytics, reporting, decision engines, and regulatory workflows across Neos wealth and asset management platforms.

This is not a dashboard-only role.

This is not just an ETL role.

You are accountable for how data flows, how secure it is, and how trustworthy it remains in production.

What You Will 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

Education

Bachelors/masters degree in computer science, Engineering, Data Science, or related field.

Required Skills & Experience

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

Solid grasp of data security fundamentals (IAM, PAM, encryption, access control)

Ability to reason about performance, cost, and reliability trade-offs

Good 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

What We Value

Engineers who think in systems, not scripts

Strong ownership of data correctness and security

Bias toward reliability over cleverness

Comfort operating in regulated environments

Engineers who debug production issues end-to-end