ATS score guide for Data Engineer at Razorpay (Go, Ruby on Rails, React, PostgreSQL) — engineering-first culture. Skills, keywords, resume mistakes, and what it takes to pass Razorpay's screening for Data Engineer roles in India. Use this guide to understand what Razorpay's ATS looks for — and check your own resume with our free AI-powered analyzer.
Check My Resume for Data Engineer at RazorpayFree · No signup required · 3 free scans
Emphasize data reliability and financial-grade pipeline engineering: 'Built a real-time transaction reconciliation pipeline using Spark Streaming and Kafka, processing 2M daily transactions across 15 banking partners with automated anomaly detection and 99.99% accuracy.' Highlight experience with data quality frameworks, pipeline testing strategies, and data governance practices. If your background includes financial services data, emphasize reconciliation, regulatory reporting, or settlement processing. List Spark, Kafka, Airflow, SQL, and Python as core skills. If transitioning from BI or reporting roles, focus on any experience building data pipelines rather than consuming data. For candidates from services companies, highlight projects involving data accuracy requirements, SLA-bound pipeline delivery, or financial data processing. Include experience with data lineage tracking, schema versioning, and data catalog tools. Razorpay values data engineers who think about the downstream consumers of their pipelines.
Data Engineers at Razorpay build the data infrastructure that processes millions of payment transactions, banking operations, and lending events daily, powering analytics, fraud detection models, regulatory reporting, and business intelligence. The data stack includes Apache Spark for batch processing, Kafka for real-time event streaming, Airflow for orchestration, and a data warehouse built on tools like Redshift or Snowflake with data lake capabilities on S3. CTCs range from 20-28 LPA for DE-1 to 38-50 LPA for senior data engineers, with ESOPs adding to total compensation. The data engineering challenges at Razorpay are shaped by the financial nature of the business — data pipelines must be accurate to the last paisa, auditable for regulatory compliance, and timely for settlement processing. Engineers build pipelines that reconcile transaction data across multiple banking partners, generate regulatory reports for RBI, and feed feature stores for real-time fraud detection models. Data quality and governance are not nice-to-haves but regulatory requirements. Bengaluru is the primary location.
These are the skills most commonly required in Razorpay's Data Engineer job descriptions. Make sure they appear verbatim in your resume to pass ATS screening.
Razorpay DE hiring managers evaluate candidates on their ability to build reliable data pipelines for financial data where accuracy and auditability are paramount. They screen for experience with Spark and Kafka, understanding of data warehouse design (dimensional modeling, slowly changing dimensions), and awareness of data quality and governance practices. Resumes that demonstrate experience building reconciliation pipelines, regulatory reporting systems, or data infrastructure for financial services stand out. Common rejection reasons include presenting data engineering as ETL job scheduling without demonstrating pipeline design thinking, no mention of data quality or testing practices for pipelines, and lack of experience with streaming architectures. For candidates from services companies doing BI reporting or data migration, the gap is typically the absence of pipeline reliability engineering — Razorpay data pipelines must guarantee exactly-once processing and produce auditable results that can withstand regulatory scrutiny.
These are the most frequent reasons Data Engineer resumes fail to pass Razorpay's ATS or get filtered during recruiter review.
Listing 'built pipelines' without data volumes, sources, or reliability metrics
Not differentiating from data science — emphasize infrastructure and reliability
Missing data quality or testing experience (Great Expectations, dbt tests)
Not featuring Go, Ruby on Rails, React prominently — Razorpay Data Engineer roles rely heavily on this stack
Razorpay values reliability — mention uptime SLAs, incident response experience, and fault-tolerant system design. Ignoring this is a common reason Razorpay resumes get filtered
The Razorpay Data Engineer interview includes a coding round (Python or Java, data processing algorithms), a SQL round (complex queries with emphasis on optimization, window functions, and handling large datasets), a data pipeline design round (design a real-time reconciliation pipeline for payment transactions across multiple banking partners), and a hiring manager round. Expect questions about handling data consistency in distributed systems, building idempotent pipelines, managing schema evolution in production, and designing audit trails for financial data. The SQL round is practical and may involve writing queries against a payment transaction schema.
SQL and Python are the foundation. Among specialized skills, Spark/distributed computing and cloud platform expertise (AWS/GCP) command the highest premiums. dbt and Airflow are increasingly table stakes. Mention specific tools with context: '40+ Airflow DAGs processing 2TB daily'.
Senior DE resumes show: platform architecture decisions, data governance frameworks, cost optimization, mentoring, and cross-team collaboration. Junior resumes focus on pipeline building. Senior bullets start with 'Designed', 'Architected', 'Led' — not 'Built' or 'Wrote'.
Razorpay is India's leading payments infrastructure company with a tech stack centered on Go, Ruby on Rails, React, PostgreSQL, Kafka. Strong engineering brand. Referral-heavy. Values deep technical understanding of distributed systems. Their culture is engineering-first culture. high bar for system reliability (payments infra). strong code review culture. For Data Engineer roles, align your resume with these priorities and highlight relevant technologies from their stack.
Razorpay's typical Data Engineer interview process: Online coding → system design deep-dive → 2 technical interviews focusing on distributed systems → cultural round. Prepare specifically for Razorpay's format — their process differs meaningfully from other companies in the industry.
Razorpay values reliability — mention uptime SLAs, incident response experience, and fault-tolerant system design. Payments domain experience is a strong advantage. Additionally, Razorpay's engineering culture emphasizes engineering-first culture — weave this into your experience descriptions. Research Razorpay's recent engineering blog posts and tech talks to reference specific initiatives or technologies they're investing in.
Dive deeper into career resources for Data Engineer roles at Razorpay.
Upload your resume + paste the Razorpay JD to get your real ATS score, missing keywords, and gap analysis.
Score My Resume FreeFree · 3 scans · No signup