Sr Data Engineer

Location:

India

At Money Gram, we're combining the strength of a trusted global brand with the agility of a tech-forward, growth driven culture. With 85+ years of experience and a presence in more than 200 countries and territories, we've built a foundation of stability and trust to help millions of people around the world send funds quickly, securely, and affordably. We're looking for bold thinkers, builders, technologists, and sellers who want real ownership of their work, thrive in collaborative environments, and are energized by solving complex challenges.

Here, you'll have the opportunity to make a measurable impact - fast. If you're eager to shape the future of cross-border payments and financial services, join us as we transform how the world moves money.

We are looking for an experienced Data Engineer with 7+ years of industry experience to design, build, and optimize scalable data pipelines on Google Cloud Platform (GCP) and AWS. The ideal candidate will have hands‑on expertise in modern ETL/ELT frameworks, data modeling, and orchestration tools, with a strong focus on performance, reliability, and automation. The candidate should be an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.

This role will collaborate closely with analytics, product, engineering and business teams to deliver high–quality data solutions that enable reporting, insights, and advanced analytics.

What you will get to do as Senior Data Engineer

• Design, develop, and maintain scalable ETL/ELT pipelines using GCP-native services such as Big Query, Cloud Composer (Airflow), Dataflow, Cloud Functions, Cloud Storage, etc.
• Build highly optimized data ingestion frameworks for batch and streaming workloads.
• Implement data transformation logic using SQL, Python, and Apache Beam.
• Design and implement partitioning, clustering, and optimization strategies in Big Query for performance and cost efficiency.
• Build reusable frameworks for ingestion, reconciliation, data quality, and metadata tracking.
• Implement data validation, profiling, and monitoring to ensure data accuracy and completeness.
• Establish best practices for error handling, logging, and alerting within pipelines.
• Support data governance initiatives, including documentation, lineage, and change management.
• Use CI/CD pipelines (Cloud Build, Git Lab CI/CD, Jenkins, etc.) to automate deployments of data pipelines.
• Work closely with Analytics, Product, and Engineering teams to gather requirements and design scalable data solutions.

• Data Engineering
  
  Experience:
  
  7+ years of experience in data engineering or related fields.
• Strong expertise in Google Cloud Platform:
  Including working knowledge of the following tools
  • Big Query
  • Cloud Composer / Airflow
  • Dataflow / Apache Beam
  • Pub/Sub
  • Cloud Storage
  • Cloud Functions
• Strong SQL skills:
  The ability to write complex, optimized queries.
• Data Pipeline Development:
  Hands‑on experience leveraging Python for data pipelines and automation.
• ETL/ELT Design:
  Experience designing and executing ETL/ELT solutions in production.
• Data Modeling:
  Solid understanding of data warehousing concepts, dimensional modeling, and analytical data structures.
• Version Control:
  Experience with Git-based version control and CI/CD pipelines.

• Domain experience in the Fintech industry.
• Experience using AWS data services such as S3 and Glue.
• Strong problem-solving skills and the ability to troubleshoot complex data issues.
• Excellent communication and documentation skills.
• Ability to work independently and manage priorities in a fast‑paced environment.
• Collaborative mindset with the ability to…