Data Engineer

We are seeking a Senior Data Engineer for the cutting-edge FinTech project from the US.

The Hiring Process

• Recruitment interview — up to 30 minutes;
• Technical interview — 1 hour;
• PM call — 30 min.

Requirements:

• 5+ years of commercial experience as a Data Engineer, with hands-on experience building and maintaining ETL pipelines
• Strong expertise in PostgreSQL, including writing, optimizing, and troubleshooting complex SQL queries in production environments
• Commercial experience with Apache Airflow, including developing, maintaining, and monitoring DAGs
• Hands-on experience with AWS data services such as RDS (PostgreSQL/Aurora), S3, EC2, CloudWatch, and ideally QuickSight
• Ability to communicate directly with clients, proactively ask questions to understand business requirements, and translate them into technical solutions
• Proven ability to work independently with minimal Business Analyst support, taking ownership of data engineering tasks from analysis to delivery
• Strong documentation skills, with experience documenting ETL pipelines, SQL scripts, workflows, and technical processes to support knowledge sharing and operational continuity
• Upper-Intermediate or higher English level

Responsibilities:

1. ETL Development & Data Pipeline Management

• Design, develop, and maintain ETL pipelines for tenant data onboarding and validation
• Build and manage the data mapping tool/ETL platform (a core product stream)
• Automate data import and transformation processes to support the goal of onboarding ~4 new tenants per quarter

1. Database Performance & Script Optimization

• Analyze and optimize long-running PostgreSQL queries that cause production performance degradation
• Rewrite and improve SQL scripts used by the client team (tenant-specific data processing scripts)
• Set up CI/CD pipelines for SQL scripts
• Address IO spikes, database locks, and replication issues

1. Apache Airflow Operations

• Configure, maintain, and develop DAGs in Apache Airflow for workflow orchestration
• Coordinate Airflow deployment and validation with the client team
• Monitor and troubleshoot Airflow pipelines in production

1. AWS Data Infrastructure

• Work with AWS services: RDS (PostgreSQL/Aurora), QuickSight, EC2, S3, CloudWatch
• Support QuickSight optimization for reporting
• Contribute to AWS cost optimization related to data services

1. Collaboration & Data Quality

• Collaborate with the client team on data processes and tenant scripts
• Ensure data integrity during tenant onboarding, payment history imports, and data cleanup
• Handle deduplication and data validation challenges in the multi-tenant environment

Відгукнутись на вакансію