GCP Data Lead

Sapsf; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Sapsf is seeking a GCP Data Lead to design, build, and maintain scalable data pipelines on Google Cloud Platform. You will own ingestion, transformation, and governance across enterprise systems, collaborating with architects, analysts, and stakeholders to deliver reliable BigQuery solutions.

You will implement batch and streaming pipelines with Dataflow, manage Cloud Composer workflows, perform data migrations from Snowflake and other warehouses, ensure data quality and lineage, and optimize

Qualifications

• Experience designing scalable data pipelines on Google Cloud Platform.
• Strong SQL and Python for data engineering, testing, and automation.
• Experience with data migration from on-premise or cloud warehouses to BigQuery.

Responsibilities

• Design and implement end-to-end data pipelines using Cloud Dataflow for batch and streaming data.
• Develop, optimize, and maintain BigQuery SPs, SQL scripts, and UDFs for transformations.
• Build and manage data orchestration workflows using Cloud Composer (Airflow).
• Establish secure connections to source systems for data ingestion and integration.
• Migrate data from Snowflake, Teradata, Netezza, Oracle, and SQL Server to BigQuery.
• Design data validation and testing frameworks for data quality across pipelines.
• Implement data governance, metadata management, lineage, and access controls.
• Collaborate with analysts and architects to define scalable data models and semantic layers in BigQuery.
• Troubleshoot pipeline failures, root-cause analysis, and preventive measures.
• Optimize cost and performance of GCP workloads using best practices.

Skills

GCP expertise

BigQuery

Dataflow

Cloud Composer

Python

SQL

ETL/ELT design

Data governance

Data modeling

Airflow

Tools

Snowflake

Teradata

Netezza

Oracle

SQL Server

Google Cloud Storage

Job description

Career Opportunities: GCP Data Lead (173569)

Requisition ID173569-Posted09/30/2026

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.

Key Responsibilities

• 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.

Skill Requirements

• 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.