Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com
We are seeking a to contribute to our next level of growth and expansion.
Job DescriptionWe are looking for a GCP Data Engineer to design, build, and maintain scalable data platforms on Google Cloud. The ideal candidate will have strong experience in automated data ingestion, analytics engineering, and MLOps, with the ability to support marketing analytics use cases and BI-driven decision making.
You will work closely with Data Science, Analytics, and Business teams to enable data-driven insights through robust pipelines, models, and reporting solutions.
You will:
- Design, develop, and maintain automated data ingestion pipelines on Google Cloud Platform (GCP)
- Build and optimize scalable data processing workflows using Spark / PySpark
- Support data science team, including data preparation, feature engineering, and experimentation support
- Develop, deploy, and maintain BI reporting and simulation tools using Looker
- Implement and manage MLOps pipelines for model training, deployment, monitoring, and retraining
- Write efficient, well-documented code in Python and SQL
- Ensure data quality, reliability, performance, and governance across data pipelines
- Collaborate with cross-functional teams including Data Scientists, Analysts, and Product stakeholders
- Strong hands-on experience with Google Cloud Platform (GCP)
- Experience supporting marketing analytics or attribution modeling use cases
- Familiarity with GCP services such as BigQuery, Dataflow, Dataproc, Cloud Composer, and Vertex AI
- Knowledge of CI/CD, version control, and cloud-native best practices
- Experience building automated data ingestion pipelines
- Proficiency in Python, Spark, PySpark, and SQL
- Experience developing and deploying Looker dashboards and BI solutions
- Solid understanding of data engineering concepts: ETL/ELT, data modeling, and pipeline orchestration
- Exposure to MLOps pipelines and lifecycle management of machine learning models
- Ability to work with large-scale datasets and distributed systems
Skills Required
- Strong hands-on experience with Google Cloud Platform (GCP)
- Experience supporting marketing analytics or attribution modeling use cases
- Familiarity with GCP services such as BigQuery, Dataflow, Dataproc, Cloud Composer, and Vertex AI
- Knowledge of CI/CD, version control, and cloud-native best practices
- Experience building automated data ingestion pipelines
- Proficiency in Python, Spark, PySpark, and SQL
- Experience developing and deploying Looker dashboards and BI solutions
- Solid understanding of data engineering concepts: ETL/ELT, data modeling, and pipeline orchestration
- Exposure to MLOps pipelines and lifecycle management of machine learning models
- Ability to work with large-scale datasets and distributed systems
Blend360 Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Blend360 and has not been reviewed or approved by Blend360.
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Fair & Transparent Compensation — Pay is considered fair-to-good by many, and public salary postings for common data roles indicate competitive packages in numerous markets. Feedback suggests overall company sentiment aligns with acceptable compensation relative to peers in consulting and analytics.
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Flexible Benefits — Flexible and remote/hybrid work arrangements are consistently highlighted in official materials and role descriptions. Feedback suggests flexibility is a meaningful part of the total rewards experience.
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Retirement Support — A 401(k) with company match is part of the core package. Feedback suggests retirement offerings are standard and contribute to a complete benefits set.
Blend360 Insights
What We Do
Our Vision is to build a company of world-class people that helps our clients optimize business performance through data, technology and analytics. Blend360 has two divisions: Data Science Solutions: We work at the intersection of data, technology and analytics. Talent Solutions: We live and breathe the digital and talent marketplace.
