Senior GCP Data Engineer Lead | Data Modernization

Long Finch Technologies

Teaneck Township (NJ)

On-site

USD 150,000 - 230,000

Full time

6 days ago

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Job summary

Long Finch Technologies in the United States seeks a Senior GCP Data Engineering Lead to guide large-scale cloud data modernization, migration, and analytics on Google Cloud. You will act as the technical anchor, collaborating with business stakeholders, architects, QA teams, and offshore delivery teams to ensure successful execution.

The role requires hands-on BigQuery, Airflow (Cloud Composer), Python, SQL optimization, and enterprise data migrations.

Qualifications

10+ years of experience in Data Engineering, Analytics, and Cloud Data Platforms.
Strong hands-on experience with Google BigQuery.
Strong hands-on experience with Cloud Composer / Apache Airflow using Python.
Advanced SQL development, debugging, and performance tuning.
Experience in large-scale Data Migration and Data Modernization programs.
Strong understanding of data modeling, ETL/ELT frameworks, and data warehousing concepts.
Experience working with structured and semi-structured datasets.
Knowledge of GCP services such as Cloud Storage, Dataflow, Dataproc, IAM, Monitoring, and Logging.
Experience with CI/CD pipelines and DevOps practices in cloud environments.
Understanding of Agile delivery methodologies.

Responsibilities

Lead end-to-end design and delivery of GCP-based data engineering and migration solutions.
Design, develop, and optimize scalable data pipelines using Cloud Composer (Airflow) and Python.
Build and manage enterprise data warehouses and analytics solutions using BigQuery.
Perform complex SQL troubleshooting, query optimization, and data validation across large datasets.
Drive data migration initiatives from legacy platforms to GCP while ensuring data integrity and regulatory compliance.
Conduct data analysis to identify quality issues, transformation requirements, and optimization opportunities.
Collaborate with business users, data architects, and cross-functional teams to translate requirements into scalable solutions.
Review code, enforce engineering best practices, and provide technical leadership to development teams.
Coordinate with QA teams to define test strategies, perform data reconciliation, and support defect resolution.
Support production deployments, troubleshooting, performance tuning, and operational excellence initiatives.