Senior Data Engineer

MoneyGram

. Design, develop, and maintain scalable ETL/ELT pipelines using GCP-native services such as BigQuery, Cloud Composer (Airflow), Dataflow, Cloud Functions, and Cloud Storage .

Posted 10/14/2026full-timeRemote • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable ETL/ELT pipelines using Google Cloud Platform services, with strong proficiency in SQL and Python for data transformation and automation. Capable of implementing data governance practices and collaborating effectively with cross-functional teams to deliver optimized data solutions.

Highest-signal resume keywords

Google Cloud PlatformETL/ELT SolutionsSQL ProficiencyPython for Data PipelinesData Warehousing Concepts

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETL/ELT Pipeline DevelopmentSQLPythonApache BeamBigQueryCloud ComposerDataflowCloud FunctionsData ValidationData Profiling

Soft Skills

Problem-SolvingCommunicationCollaborationIndependenceTime Management

Tools & Technologies

Cloud BuildGitLab CI/CDJenkinsCloud StoragePub/Sub

Industry Keywords

FintechData GovernanceDimensional ModelingAnalytical Data Structures

Tech Stack

Tools & technologies

AirflowApacheAWSBigQueryCloudETLGoogle Cloud PlatformJenkinsPythonSQL

About the role

Key responsibilities & impact

Design, develop, and maintain scalable ETL/ELT pipelines using GCP-native services such as BigQuery, Cloud Composer (Airflow), Dataflow, Cloud Functions, and Cloud Storage
Build optimized data ingestion frameworks for batch and streaming workloads
Implement data transformation logic using SQL, Python, and Apache Beam
Design and implement BigQuery partitioning, clustering, and optimization strategies 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 such as Cloud Build, GitLab CI/CD, and Jenkins to automate data-pipeline deployments
Collaborate with Analytics, Product, Engineering, and business teams to gather requirements and design scalable data solutions

Requirements

What you’ll need

7+ years of experience in data engineering or related fields
Strong expertise in Google Cloud Platform, including BigQuery, Cloud Composer/Airflow, Dataflow/Apache Beam, Pub/Sub, Cloud Storage, and Cloud Functions
Strong SQL skills, including writing complex, optimized queries
Hands-on experience using Python for data pipelines and automation
Experience designing and executing ETL/ELT solutions in production
Solid understanding of data warehousing concepts, dimensional modeling, and analytical data structures
Experience with Git-based version control and CI/CD pipelines
Domain experience in the Fintech industry (nice to have)
Experience using AWS data services such as S3 and Glue (nice to have)
Strong problem-solving skills and 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 ability to work cross-functionally