Google Cloud Platform Data Engineer *** Direct End Client ***

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 6 Month(s)

Skills

Akka
Apache Kafka
Apache Spark
Artificial Intelligence
C++
Data Engineering
Data Flow
Data Governance
Data Modeling
Machine Learning Operations (ML Ops)
Machine Learning (ML)
SQL
Python
Software Development
GCP data engineer
GCS
BigQuery
VertexAI
Streaming
Machine Learning
MLOps
Google Cloud Platform
GCP
Dataflow
Composer
Airflow
Vertex AI
Bigtable
Pub/Sub
Scala
Spark
Kafka
CI/CD
Feature Engineering
Streaming Data
Data Pipelines
Monitoring
Logging
Alerting
Cloud Infrastructure
Jupyter
Technical Leadership
Code Reviews
Agile
Scrum
ETL
Data Storage Optimization
Cross-functional Collaboration
Data Quality
Data Discovery
GRPC
Akka-Http
ORM
Web Application Internals
Deployment Strategies

Job Details

We are seeking a highly skilled and motivated Senior Data Engineer to join our team and lead the development of scalable data infrastructure and machine learning pipelines on Google Cloud Platform (Google Cloud Platform). This role involves close collaboration with Data Scientists, ML Engineers, and cross-functional teams to build robust data solutions that power personalization, analytics, and intelligent decision-making.

< id="keyresponsibilities">Key Responsibilities:</>
  • Design, build, and maintain scalable and efficient data pipelines using Google Cloud Platform services such as BigQuery, Dataflow, and Composer.
  • Develop and enhance Python-based frameworks and libraries to support data processing, analysis, and machine learning operations.
  • Collaborate with cross-functional teams to gather requirements, provide technical guidance, and implement end-to-end data solutions.
  • Build and scale feature platforms for multiple entities (user/item/model-based features) with strong governance, monitoring, and discovery capabilities.
  • Lead the design and development of streaming data platforms using Scala, Pub/Sub, Akka, and Dataflow.
  • Optimize data storage and retrieval using technologies like Bigtable and Vertex AI Feature Store to support ML modeling.
  • Implement robust monitoring, logging, and alerting systems to ensure reliability and performance of data infrastructure.
  • Contribute to shared tooling and standards to improve productivity and consistency across the Data Engineering team.
  • Mentor junior engineers and participate in code reviews and technical design discussions.
< id="requiredqualifications">Required Qualifications:</>
  • Bachelor s degree (or foreign equivalent) in Computer Science, Engineering, Information Systems, Mathematics, Physics, or a related field.
  • Minimum 5 years of experience in data engineering, software development, or related roles.
  • Strong programming skills in Python and at least one server-side OOP language (Scala, Java, C++).
  • Hands-on experience with Google Cloud Platform services including BigQuery, Dataflow, Pub/Sub, Composer, Bigtable, and Vertex AI.
  • Deep understanding of data modeling, algorithms, design patterns, and scalable architecture.
  • Experience with production infrastructure tools such as Kafka, Spark, Akka-Http, GRPC, and SQL-based databases.
  • Familiarity with Agile/Scrum development practices and CI/CD pipelines.
< id="preferredskills">Preferred Skills:</>
  • Experience with MLOps frameworks and deploying ML models in production.
  • Knowledge of web application internals and deployment strategies.
  • Strong understanding of data governance, lineage, and compliance frameworks.
Data Engineering, Machine Learning, MLOps, Google Cloud Platform, Google Cloud Platform, BigQuery, Dataflow, Composer, Airflow, Vertex AI, Bigtable, Pub/Sub, Akka, Python, Scala, Spark, Kafka, CI/CD, Feature Engineering, Streaming Data, Data Pipelines, Data Modeling, Data Governance, Monitoring, Logging, Alerting, Cloud Infrastructure, Jupyter, Technical Leadership, Code Reviews, Agile, Scrum, ETL, Data Storage Optimization, Cross-functional Collaboration, Data Quality, Data Discovery, GRPC, Akka-Http, SQL, ORM, Web Application Internals, Deployment Strategies
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