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Protocol Intelligence
Data-driven signals on your job's competitivenessUnicorn fintech brand, popular Data Engineer title, mid-level experience, metro location, and broad tooling needs increase competition.
Core data engineering skills (SQL, Python, cloud, Airflow) are highly transferable across industries despite fintech domain preference.
Explicit 2–3 years plus mandatory SQL, Python, AWS, Redshift, and Airflow skills imply high filter strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Build and optimise scalable, maintainable, high-performance data pipelines and workflows for real-time cross-border payments.
Lead cloud migration efforts by evolving data architectures on AWS, leveraging tools like Airflow, Redshift, dbt, and Kafka.
Collaborate with global teams translating business requirements into robust data solutions ensuring data quality, security, and reliability in a mission-critical environment.
Minimum Requirements
2–3 years of professional experience in Data Engineering or related role.
Strong expertise in SQL including query optimisation and data modelling; solid Python skills for data pipeline development.
Hands-on experience with AWS services (Redshift, Lambda, Glue, S3) and Airflow; familiarity with dbt for transformations.
Work Experience Required: 2–3 years; Location: India-based role; Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in designing and operating cloud-based data platforms, familiar with transitioning from on-premises to AWS cloud environments.
Comfortable working with real-time data streams and large-scale data migrations in fintech or payments domain.
Capable of working cross-functionally across globally distributed teams to deliver scalable and reliable data infrastructure solutions.