Data Engineer – Privacy Infrastructure & Metadata Systems

Intelliswift - An LTTS Company; United States; Remote; USD 100,000 - 720,000; Full time

Job summary

A leading company is seeking a Data Engineer for their Privacy and Metadata Systems team. This role focuses on building scalable data pipelines and ensuring data privacy across a large-scale platform. The ideal candidate will have strong experience in Python and data processing, making a significant impact on data governance and quality.

Qualifications

• 3-5 years of experience as a Data Engineer.
• Proficiency in data processing frameworks.
• Ability to design reliable and scalable data systems.

Responsibilities

• Design and maintain data pipelines for ingestion and discovery.
• Migrate data from legacy systems to distributed databases.
• Perform monitoring of batch and real-time data systems.

Skills

Python

Data Processing

ETL Pipelines

Data Modeling

Communication

Education

Bachelor's Degree in Computer Science or related field

Tools

Tableau

Looker

Grafana

Job description

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Intelliswift - An LTTS Company provided pay range

This range is provided by Intelliswift - An LTTS Company. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$75.00/hr - $85.00/hr

Direct message the job poster from Intelliswift - An LTTS Company

Director - Technical Recruitment at Intelliswift Software, Inc.

Location: Remote - Central time Preferred

Duration: 6 Months to start with

W2 Contract only

We are looking for a Data Engineer to join our Privacy and Metadata Systems team, focusing on building scalable data pipelines, dashboards, and infrastructure to improve data privacy, governance, and annotation workflows. This role will directly impact how our systems handle sensitive data, metadata quality, and labeling practices across a large-scale data platform

Responsibilities:

• Design, build, and maintain data pipelines to support label ingestion, annotation, and discovery workflows.
• Migrate and optimize data pipelines from legacy storage systems to modern, distributed databases.
• Conduct performance tuning and monitoring of batch and real-time data ingestion systems.

Metadata & Label Governance

• Analyze label usage data to identify unused or outdated labels and recommend deprecation strategies.
• Improve label metadata and semantic descriptions to align with internal standards.
• Generate dashboards and insights to monitor metadata quality and labeling accuracy.

Privacy & Compliance Infrastructure

• Perform gap analyses to ensure taxonomy coverage aligns with evolving data privacy and regulatory standards.
• Contribute to architecture that enforces compliance across data assets and annotations.
• Build automated monitoring and alerting for ingestion reliability and policy violations.
• Develop intuitive dashboards for internal stakeholders to track system health, labeling trends, and ingestion performance.
• Work closely with product and engineering teams to prioritize and visualize critical KPIs and service metrics.
• Build mechanisms to surface and prioritize root causes of labeling or data quality failures.
• Define best practices for multi-label annotations and communicate governance changes to impacted teams.
• Partner with stakeholders to gather requirements for new data tooling and label discovery features.
• Support engineering audits and contribute to internal documentation and frameworks.

Required Qualifications:

• 3–5 years of experience as a Data Engineer or Software Engineer working with large-scale data infrastructure.
• Proficiency in Python and data processing frameworks.
• Experience building and optimizing ETL pipelines, with strong data modeling and analytical skills.
• Ability to independently design, implement, and monitor reliable and scalable data systems.
• Strong verbal and written communication skills; able to work cross-functionally with technical and non-technical teams.

Nice to Have:

• Experience with dashboarding tools (e.g., Tableau, Looker, Grafana, or custom-built dashboards).
• Understanding of privacy-enhancing technologies or data governance frameworks.
• Exposure to event-driven architecture or distributed databases.
• Familiarity with data lineage, annotation systems, or metadata cataloging tools.

Seniority level

• Seniority level

  Associate

Employment type

• Employment type

  Contract

Job function

• Industries

  Technology, Information and Media

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