- Location
- Bengaluru, Karnataka
- Type
- Full-time
- Department
- Engineering
- Experience
- 5+ years
- Education
- Bachelor
- Source
- RecruiterFlow
Description
Recruiterflow brings AI-native intelligence and enterprise-grade depth to executive search and recruiting businesses worldwide. Over 1,700 agencies and 6,000+ recruiters across 90+ countries trust us to power their operations—from candidate sourcing to deal closure.We’re led by second-time founders who’ve spent 13 years at the forefront of AI. We’re bootstrapped and profitable—growing on revenue, not venture capital. Our customers fund our roadmap because what we build actually works. We’ve launched industry-first capabilities repeatedly, and we’re not slowing down. We’re top 3 today. We’re building to be number one.
We are looking for a highly skilled Data Migration Engineer to join our growing engineering team. In this role, you will be responsible for building scalable data pipelines, managing data migration initiatives, and developing reliable cloud-native data solutions that power critical business functions. You will collaborate across teams, drive technical decisions, and ensure data quality, integrity, and performance across our platform.
Join us if you want to solve complex data challenges while building products that transform the recruiting industry.
Join us if you want to solve complex data challenges while building products that transform the recruiting industry.
Job Responsibilities:
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows.
- Design and build reusable, idempotent migration frameworks that can rapidly ingest, map, and transform highly variable schemas from legacy competitor platforms.
- Extract, transform, validate, and load large datasets while ensuring data accuracy and consistency.
- Build automation and tooling to improve data processing efficiency and reliability.
- Build robust error-handling, logging, and automated reconciliation reports to prove data fidelity to incoming customers.
- Collaborate with engineering, product, and business teams to define data requirements and solutions.
- Monitor, troubleshoot, and optimize data workflows for performance and scalability.
- Implement data quality checks, validation frameworks, and governance best practices.
- Contribute to architecture discussions and technical decision-making.
- Mentor junior engineers and contribute to engineering best practices.
- Create and maintain technical documentation for data systems and processes
Qualifications:
- Bachelor's degree in Computer Science, Engineering, or a related field.
- 5+ years of experience in Data Engineering or related roles.
- Strong proficiency in Python for data processing and automation.
- Hands-on experience with AWS services and cloud-based data architectures.
- Strong expertise in designing and implementing ETL/ELT pipelines.
- Experience working with large-scale datasets and distributed data processing systems.
- Deep expertise in SQL and schema design, with a strong understanding of relational databases (e.g., MySQL/PostgreSQL) and query optimization.
- Understanding of data modeling, data migration, and data quality best practices.
- Excellent problem-solving, communication, and collaboration skills.
Nice to Have:
- Experience with modern data warehouses and analytics platforms.
- Experience with workflow orchestration tools such as Airflow.
- Exposure to AI/ML data pipelines and data-intensive SaaS products.
- Experience working in a high-growth product company environment.
Skills
PythonAWSSQLPostgreSQLMySQLAirflowData EngineeringETL
