Design and implement data privacy pipelines while ensuring compliance with regional regulations and improving data quality within a collaborative compliance framework.
Job Description
What You Will Do
- Perform data inspection, classification, and profiling on regional datasets to assess sensitivity and compliance requirements.
- Design and implement data desensitization, masking, anonymization, and pseudonymization pipelines prior to ingestion and exposure.
- Build and maintain clean, compliant, and well-documented datasets for downstream analytics and reporting.
- Support user-level and aggregated (fine-to-coarse) data analysis in compliance with regional data regulations.
- Collaborate with data governance, security, and legal/compliance teams to translate regulatory requirements into technical controls and data workflows.
- Enforce compliance-by-design principles: no desensitization → no ingestion; no inspection → no exposure.
- Contribute to continuous improvement of data quality, data lineage, metadata management, and auditability.
- Participate in platform construction and administration under strict controls (e.g., RBAC, MFA, IP allowlists, separation of duties).
Skills, Qualifications, and Experience We Look For
- 3–5 years of experience as a Data Engineer or in a closely related role.
- Strong hands-on experience with data pipelines, ETL/ELT, and data warehousing (e.g., Spark, SQL, Airflow, Kafka, Hive, or equivalent).
- Solid understanding of data cleaning, validation, and quality assurance techniques.
- Practical experience handling sensitive or regulated data (PII, user-level data, financial, or operational data).
- Working knowledge of data compliance concepts and regional regulations, such as SOC2, HIPPA, PDPA, GDPR, EO14117, or similar frameworks.
- Proficiency in SQL and at least one programming language (Python preferred).
Preferred
- Experience with data masking, anonymization, or privacy-preserving analytics.
- Familiarity with data governance frameworks, metadata management, and audit logging.
- Experience operating in multi-region or cross-border data environments.
- Exposure to cloud-based data platforms (AWS, GCP, Azure) and security best practices.
- Prior collaboration with legal, compliance, or security teams.
Fuku is focused on streamlining the transition from legacy systems to modern programming languages, offering enterprise-level AI solutions that also cover code maintenance and documentation. Our services cater to organizations looking to enhance their technological infrastructure and efficiency in a rapidly evolving digital landscape.
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