DATA ANALYTICS ENGINEER
Fintech / Financial Services / Full-Time / 5+ Years Experience

Experience- 5 to 8 Years
Notice Period- Immediate to 15 Days.
Work mode- Hybrid
Location- Pune/ Bangalore/Hyderabad/ Noida/ Gururgram

Role Summary

We are seeking an experienced Data Analytics Engineer to design, build, and optimize scalable data pipelines and analytics infrastructure that power critical financial products and decisions. You will work at the intersection of software engineering and data analytics — building reliable ETL/ELT pipelines, orchestrating cloud-native workflows, and enabling trusted, high-quality data for reporting, risk, and product teams. This role requires robust engineering discipline (version control, CI/CD, infrastructure-as-code) combined with deep SQL and PySpark expertise, ideally within a regulated banking or financial services environment.

Key Responsibilities
Design, build, and maintain scalable, reliable ETL/ELT data pipelines across cloud and on-prem sources, ensuring data quality, lineage, and auditability.




Develop and optimize Python/ PySpark and SQL-based data transformations for large-scale, high-volume financial datasets.
Architect and manage data pipeline orchestration (e.g., Airflow, Databricks Workflows, Step Functions) to automate ingestion, transformation, and delivery.
Build and maintain CI/CD pipelines using GitHub/GitHub Actions to support automated testing, deployment, and version-controlled infrastructure changes.
Develop cloud-based solutions on AWS (S3, Glue, EMR, Redshift, Lambda, IAM) supporting analytics, reporting, and downstream ML use cases.
Deploy and manage infrastructure and pipelines as code, following best practices for environment promotion, rollback, and monitoring.
Monitor, troubleshoot, and optimize pipeline performance, query efficiency, and cost across the data stack.
Partner with data scientists, analysts, product, and risk/compliance teams to translate business requirements into robust data solutions.

📌 Data Engineer (India)
🏢 EXL
📍 India