Senior Data Engineer

Responsibilities

• Own day-to-day operations of data platforms, including capacity management, stability, upgrades, and recovery drills.
• Design and manage multi-source data ingestion from exchanges and internal/external systems with robust retry mechanisms.
• Develop rule-based and statistical data quality checks for completeness, uniqueness, and anomaly detection.
• Plan and maintain scalable ETL/ELT pipelines supporting both batch and real-time streaming.
• Implement automated remediation, reconciliation workflows, and historical backfilling.
• Enforce data access controls, encryption, and auditing to comply with regulatory requirements and PII management.
• Apply Infrastructure-as-Code, data versioning, and CI/CD to improve pipeline predictability.
• Contribute to embedded GenAI and LLM-powered data applications for enterprise analytics and productivity.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
• 5+ years of experience in data engineering, data platform architecture, or AI/ML engineering.
• Strong experience with modern cloud data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
• Proficiency in SQL and workflow orchestration tools like Airflow.
• Hands-on experience with streaming platforms such as Kafka.
• Familiarity with GitLab and CI/CD pipelines.
• Solid understanding of data warehouse development lifecycles and dimensional modeling.
• Working knowledge of data governance, lineage, privacy, and security frameworks.

About the Company

AIFT is building advanced data-driven solutions and enterprise-grade AI applications to power analytics and decision-making in regulated environments.