Google Cloud Platform – Data Engineer
Listed on 2026-01-01
-
Engineering
Data Engineer -
IT/Tech
Data Engineer
Miracle Software Systems Inc. is seeking a Data Engineering Engineer 2 – Google Cloud Platform Data Engineer for one of our clients at our Dear Born, Michigan,USA location. The candidate must have experience with Google Cloud Platform, ETL, Apache Spark, Data Architecture, Python, SQL, KAFKA skills
. This is an Onsite position at the Dear Born, Michigan location. Kindly let me know your availability for this position and share any referrals if you have.
Job Title:
Data Engineering Engineer 2 – Google Cloud Platform Data Engineer
Location:
Dear Born, Michigan
Experience Level: 8- 10 years
Skills :
Google Cloud Platform, ETL, Apache Spark, Data Architecture, Python, SQL, KAFKA
Employees in this job function are responsible for designing, building, and maintaining data solutions including data infrastructure, pipelines, etc. for collecting, storing, processing and analyzing large volumes of data efficiently and accurately
Key ResponsibilitiesCollaborate with business and technology stakeholders to understand current and future data requirements
Design, build and maintain reliable, efficient and scalable data infrastructure for data collection, storage, transformation, and analysis
Plan, design, build and maintain scalable data solutions including data pipelines, data models, and applications for efficient and reliable data workflow
Design, implement and maintain existing and future data platforms like data warehouses, data lakes, data lakehouse etc. for structured and unstructured data
Design and develop analytical tools, algorithms, and programs to support data engineering activities like writing scripts and automating tasks
Ensure optimum performance and identify improvement opportunities
Google Cloud Platform, ETL, Apache Spark, Data Architecture, Python, SQL, KAFKA
Experience Preferred- Data Pipeline Architecture & Development:
Design, build, and maintain highly scalable, fault-tolerant, and performant data pipelines to ingest and process data from 10 siloed sources, including both structured and unstructured formats. - ML-Driven ETL Implementation:
Operationalize ETL pipelines for intelligent data ingestion, automated cataloging, and sophisticated normalization of diverse datasets. - Unified Data Model Creation:
Architect and implement a unified data model capable of connecting all relevant data elements across various sources, optimized for efficient querying and insight generation by AI agents and chatbot interfaces. - Big Data Processing:
Utilize advanced distributed processing frameworks (Apache Beam, Apache Spark, Google Cloud Dataflow) to handle large-scale data transformations and data flow. - Cloud-Native Data Infrastructure:
Leverage Google Cloud Platform services to build and manage robust data storage, processing, and orchestration layers. - Data Quality, Governance & Security:
Implement rigorous data quality gates, validation rules, bad record handling, and comprehensive logging. Ensure strict adherence to data security policies, IAM role management, and Google Cloud Platform perimeter security. - Automation & Orchestration:
Develop shell scripts, Cloud Build YAMLs, and utilize Cloud Scheduler/Pub Sub for E2E automation of data pipelines and infrastructure provisioning. - Collaboration with AI/ML Teams:
Work closely with AI/ML engineers, data scientists, and product managers to understand data reqts, integrate data solutions with multi-agentic systems, and optimize data delivery for chatbot functionalities. - Testing & CI/CD:
Implement robust testing strategies, maintain high code quality through active participation in Git/Git Hub, perform code reviews, and manage CI/CD pipelines via Cloud Build. - Perf. Tuning & Optimization:
Continuously monitor, optimize, and troubleshoot data pipelines and BQ performance using techniques like table partitioning, clustering, and sharding.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).