Data Engineer

Apollo Solutions; New York (NY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Apollo Solutions is recruiting a hands-on Data Engineer to strengthen data protection across a complex cloud environment. You will work with data, engineering and cybersecurity specialists to build practical solutions in a regulated industry, focusing on discovery, classification and access controls.

You'll implement DSPM capabilities and develop Python/SQL integrations, APIs and custom connectors, with dashboards to monitor protection coverage and remediation needs.

Qualifications

• 5+ years in data engineering, software engineering, security engineering or related discipline.
• ≥2 years implementing practical data protection capabilities (discovery, classification, masking, tokenization or access controls).
• Strong Python and SQL skills, with evidence of automation and platform integrations.
• Hands-on with cloud data environments such as AWS, GCP or Databricks.

Responsibilities

• Build automated workflows to discover and classify sensitive information across structured and unstructured data.
• Implement masking, tokenization and other controls protecting data while enabling use.
• Develop DSPM capabilities to identify exposure and gaps in protection.
• Write Python and SQL integrations, APIs and custom connectors across cloud data platforms.
• Create monitoring and dashboards showing controls in place and action needed.
• Take solutions through development, testing, deployment and ongoing operation with good software practices.
• Help engineering teams and data owners adopt the tools built.

Skills

Python

SQL

DSPM concepts

Data protection

Tools

APIs

CI/CD

Custom connectors

Job description

Hybrid | Three days per week in the office

Our client is an established financial services organisation investing in its cloud data capabilities and the engineering needed to keep sensitive information secure. You'll work alongside data, engineering and cybersecurity specialists to build practical solutions in an environment where reliability and trust matter. Previous financial services experience would be useful, although candidates from other regulated industries are also welcome.

Build the tools that make sensitive data safer to use.

We're recruiting a hands-on Data Engineer to strengthen data protection across a complex cloud environment. This role combines Python and SQL engineering with practical security challenges: finding sensitive information, controlling how it is exposed, and automating protection as data moves between platforms.

You'll work closely with engineering, cybersecurity and governance teams, turning requirements into working software. Your impact will be visible through better protection coverage, faster remediation and fewer manual processes.

What you'll do

• Build automated workflows to discover and classify sensitive information across structured and unstructured data.
• Implement masking, tokenization and other controls that protect data while supporting its use.
• Develop Data Security Posture Management (DSPM) capabilities to identify exposure, misconfigurations and gaps in protection.
• Write Python and SQL integrations, APIs and custom connectors across cloud data platforms.
• Create monitoring and dashboards that show where controls are working and where action is needed.
• Take solutions through development, testing, deployment and ongoing operation, using sound software engineering practices.
• Help engineering teams and data owners adopt the tools you build.

What you'll bring

• At least five years' experience in data engineering, software engineering, security engineering or a related discipline.
• At least two years implementing practical data protection capabilities, such as discovery, classification, masking, tokenization or access controls.
• Strong Python and SQL skills, with evidence of building automation and platform integrations.
• Hands-on experience with cloud data environments such as AWS, GCP or Databricks.
• An understanding of sensitive data exposure, DSPM principles and how to remediate protection gaps.
• Experience with APIs, CI/CD, automated testing and supporting production systems.
• The ability to explain technical findings clearly and work across engineering and business teams.

Experience with enterprise data security or governance platforms, metadata management, data lineage or regulated environments would be useful.