Data Engineer

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.