• Support cloud-based data pipelines for ingestion, transformation, and storage. • Work with AWS services to help maintain and improve data workflows. • Help with data validation, monitoring, and troubleshooting of analytics pipelines. • Contribute to data lake solutions used for reporting and analytics. • Support reporting and visualization tools used by business partners. • Follow best practices for source control, documentation, and team collaboration.

• Design, build, and maintain **scalable, reliable, and high-performance data pipelines** • Develop end-to-end **ETL / ELT workflows** • Process large-scale datasets using **Spark / PySpark** • Build and orchestrate cloud-native pipelines in **AWS and/or Azure** • Design and optimize **Snowflake data warehouse solutions** • Ensure **performance, scalability, governance, and cost optimization** • Write and optimize **advanced SQL queries** • Collaborate with **Data Scientists, Analysts, and Software Engineers** • Translate business requirements into **production-ready data solutions** • Ensure **data consistency, availability, and quality** • Implement **CI/CD, Git workflows, and Dockerized deployments** • Improve reliability and observability of data platforms

We love technology, and we enjoy what we do. We are always looking for innovation. We have social awareness and strive to improve it daily. We make things happen. You can trust us. Our Enrouters are always up for a challenge. We ask questions, and we love to learn. We pride ourselves on having great benefits and compensations, a fantastic work environment, flexible schedules, and policies that positively impact the balance of work and life outside of it. At Enroute, we are looking for a Senior Data Engineer to join a growing Data team responsible for designing, building, and evolving scalable data platforms and cloud-native pipelines that support business intelligence, analytics, and operational workloads. The ideal candidate is highly hands-on with Python, Spark/PySpark, Snowflake, and cloud-based data architectures, with strong experience building reliable, production-grade ETL/ELT pipelines and modern data warehousing solutions. This role is ideal for someone who enjoys solving complex data challenges, optimizing performance at scale, and collaborating closely with data scientists, analysts, and engineering teams.

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards. WHY JOIN US If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you! ABOUT THE ROLE WHAT YOU WILL DO - Build and maintain scalable, distributed, fault-tolerant data pipelines on GCP; - Develop and manage lakehouse layers and Delta Lake workflows using BigQuery and Dataproc; - Collaborate with stakeholders across data engineering, compliance, and business teams; - Design and implement pipelines to acquire, normalise, transform, and release large volumes of financial data; - Design and implement bitemporal data models on BigQuery for regulatory-grade time-series datasets; - Build and maintain testing frameworks for data pipelines and transformation logic; - Own end-to-end solutions including ingestion pipelines, QA workflows, correction management, and audit trails; - Contribute to shared platform services in a collaborative environment; - Support implementation of AI solutions including data ingestion, anomaly detection, and semantic search using Vertex AI. MUST HAVES - 6–8 years of experience in data engineering; - Proficiency in Python for data pipelines, transformation logic, and automation; - Proficiency in SQL with hands-on experience in BigQuery including partitioning, clustering, and time-series queries; - Experience with Cloud Composer (Apache Airflow) for pipeline orchestration; - Working knowledge of Dataproc (Apache Spark) for batch ingestion and incremental processing; - Experience with AI-assisted development tools such as GitHub Copilot or similar; - Experience with Git version control and collaboration workflows; - Familiarity with REST APIs for integrations; - Familiarity with GCP technologies (Cloud Storage, Pub/Sub, Datastream, Cloud Monitoring, IAM, VPC Service Controls); - Understanding of financial data concepts related to equities and& other asset classes; - Upper-intermediate English level. NICE TO HAVES - Knowledge of data libraries such as pandas or PySpark; - Experience with columnar storage and time-series analytics tools such as ClickHouse; - Familiarity with Dataplex for data governance and lineage; - Understanding of Change Data Capture (CDC) using Datastream; - Understanding of bitemporal data modeling concepts; - Knowledge of financial reference data such as equities, fixed income, or corporate actions; - Experience with BigQuery cost management techniques; - Experience with CI/CD pipelines and Terraform for infrastructure as code; - Exposure to LLMs and& Agentic AI using Vertex AI for data-related use cases. PERKS AND BENEFITS - Remote work & Local connection: Work where you feel most productive and connect with your team in periodic meet-ups to strengthen your network and connect with other top experts. - Legal presence in India: We ensure full local compliance with a structured, secure work environment tailored to Indian regulations. - Competitive Compensation in INR: Fair compensation in INR with dedicated budgets for your personal growth, education, and wellness. - Innovative Projects: Leverage the latest tech and create cutting-edge solutions for world-recognized clients and the hottest startups.