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# Senior GCP Data Engineer

- **Company:** Danta Technologies
- **Location:** Secaucus, NJ, United States (Remote available)
- **Experience:** Expert
- **Salary:** $93,600.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Airflow, Data Analysis, Apache HTTP Server, Business Logic, BigQuery, Cloud Computing, Cloud Database, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Migration, Data Systems, Data Warehousing, Data Flow Control, Python (Programming Language), Metadata, Meta-Data Management, Microsoft SQL Server, Oracle (Applications), Performance Tuning, Systems Development Life Cycle, User Defined Functions, SQL Stored Procedures, SQL Databases, Data Streaming, Teradata SQL, Scripting, Google Cloud, Data Ingestion, Netezza, Snowflake, Data Layers, Data Lineage, Data Management, Data Pipelines, Apache Beam
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-gcp-data-engineer-secaucus-nj--011420ef-ebe2-47b4-b88d-0f7ff6313d3e

## About the Role

GCP (Good Clinical Practices), GCP (Good Clinical Practices), Data Management, Data Analysis, Cloud Computing, Performance Tuning/Optimization, Scalable System Development, Architectural Analysis, Python Programming/Scripting Language, Apache, * Strong hands-on experience in Google Cloud Platform (GCP) with expertise in BigQuery, Dataflow, Cloud Composer, and GCS.

 * Proficient in Python programming for data engineering (Dataflow pipelines, validation scripts, automation).
 * Expertise in BigQuery SQL, Stored Procedures, Views, and User Defined Functions (UDFs).
 * Experience with data migration from on-premise or cloud data warehouses (preferably Snowflake, Teradata, Netezza, Oracle, SQL Server) to BigQuery.
 * Strong understanding of ETL/ELT frameworks, data modeling, and schema design (Star/Snowflake).
 * Familiarity with data governance, metadata, and lineage frameworks on GCP.
 * Knowledge of data validation and testing techniques, including reconciliation, rule-based checks, and automation.
 * Hands-on experience in workflow orchestration using Cloud Composer (Airflow) with custom operators.
 * Strong SQL tuning and BigQuery performance optimization skills.
 * Good communication and collaboration skills to work with cross-functional teams in Agile environments.
 * Proven ability to troubleshoot, optimize, and enhance complex data workflows at scale.

## Description

The Senior Data Engineer will be responsible for designing, developing, and maintaining scalable data pipelines and solutions on Google Cloud Platform (GCP). The role focuses on data ingestion, transformation, orchestration, and governance across enterprise data systems. The engineer will work closely with architects, data analysts, and business stakeholders to implement high-quality, performance-optimized data solutions in BigQuery and related GCP services., * Design and implement end-to-end data pipelines using Cloud Dataflow (Python/Apache Beam) for batch and streaming data.

 * Develop, optimize, and maintain BigQuery stored procedures (SPs), SQL scripts, and user-defined functions (UDFs) for complex transformations and business logic implementation.
 * Build and manage data orchestration workflows using Cloud Composer (Airflow) with appropriate operators and dependencies.
 * Establish secure and efficient connections to source systems for data ingestion and integration.
 * Manage data ingestion workflows from on-premise and cloud sources into Google Cloud Storage (GCS) and BigQuery.
 * Execute history data migration from legacy data warehouses (preferably Snowflake, Teradata, Netezza, Oracle, SQL Server) to BigQuery, ensuring accuracy and performance optimization.
 * Design and maintain data validation and testing frameworks for ensuring data quality and reliability across pipelines.
 * Implement data governance practices, including metadata management, lineage tracking, and access control.
 * Collaborate with data analysts and architects to define scalable and reusable data models, views, and semantic layers in BigQuery.
 * Troubleshoot data pipeline failures, perform root cause analysis, and implement preventive measures.
 * Optimize cost and performance of GCP workloads using best practices for BigQuery and Dataflow.