Description
Role Overview :
As a Senior Data Engineer / Growth Data Engineer at PayMeIndia, you will play a critical role in shaping our data platform and analytics ecosystem. You will work closely with Product, Engineering, Risk, Operations, and Business teams to design, build, and maintain scalable data pipelines and analytical systems that power insights, automation, and strategic decision-making.
Your work will directly influence product growth, customer experience, risk management, and revenue optimization.
Key Responsibilities
- Partner with product, business, and engineering teams to translate business requirements into scalable data solutions.
- Design, build, and maintain reliable ETL/ELT pipelines from multiple data sources.
- Develop high-quality, well-modeled datasets for reporting, dashboards, and advanced analytics.
- Ensure data accuracy, completeness, and consistency using automated validation and monitoring frameworks.
- Implement data governance, privacy, and security best practices for financial and user data.
- Build reusable data frameworks, libraries, and tooling to enable self-service analytics.
- Optimize performance of batch and streaming data pipelines.
- Troubleshoot and resolve data quality, latency, and pipeline failures
What We Are Looking For
- Bachelors or Masters degree in Computer Science, Engineering, Statistics, or related field (or equivalent experience).
- 5+ years of experience building and managing data systems at scale.
- Strong programming skills in Python (or Scala/Java) and advanced SQL.
- Experience with modern data warehouses such as BigQuery, Snowflake, or Redshift.
- Experience with orchestration tools such as Airflow.
- Hands-on experience with Spark, Databricks, Kafka, or similar processing frameworks.
- Strong understanding of data modeling, schema design, and performance optimization.
- Experience working on cloud platforms such as AWS, GCP, or Azure.
Nice To Have
- Experience in fintech, payments, lending, or financial analytics.
- Familiarity with BI and visualization tools like Looker, Tableau, or Superset.
- Experience with event tracking systems such as Segment, RudderStack, or Snowplow.
- Knowledge of experimentation, growth analytics, and A/B testing frameworks.
(ref:hirist.tech)
