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Salary
≈ $20k – $41k per year (Estimated)
Location
Remote (India)
Seniority
Senior · 7+ years exp

Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Oct 12, 2026.

Overview
Company
Impact
Profile match
MoneyGram operates a global money transfer network spanning agents and digital channels. Customers send remittances to bank accounts, mobile wallets and cash pickup locations. The company has invested heavily in shifting volume to its app.

Job Title: Senior Data Engineer

Location: India, Remote

 

About the Role

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 BigQuery, 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 BigQuery 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, GitLab 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.

What you will need to be successful

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

BigQuery

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.

Nice to have experience

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 work cross-functionally.

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