Overview
$60
Accepts corp to corp applications
Contract - Long Term
Skills
Python
Database
DEV OPS
Governance
Tableau Software
SQL
ETL
Business Intelligence
Machine Learning
Git
Continuous Integration/Delivery
Apache
GitHub
Problem Solving
Terraform
GCP
Kafka
Hive
Apache Kafka
Welding
Real-Time
Pipeline
Version Control
Hadoop
BigQuery
Google Analytics
Control Systems
digital marketing
Digital Campaign
Batch Processing
Job Details
Title: Google Cloud Platform Data Engineer
Experience: 8+ Years
Location: Remote
Note:Need eCommerce Domain
Primary Skills- PySpark, Spark, Python, Big Data, Google Cloud Platform, Apache Beam, Dataflow, Airflow, Kafka and BigQuery
Good to Have: GFO, Google Analytics
Job Description:
- 7-10 years experience as a data warehouse engineer/architect designing and deploying data systems in a startup environment
- Mastery of database and data warehouse methodologies and techniques from transactional databases to dimensional data modeling, to wide deformalized data marts
- Deep understanding of SQL-based Big Data systems and experience with modern ETL tools
- Expertise in designing data warehouses using Google Big Query
- Experience developing data pipelines in Python
- A firm believer in data-driven decision-making, and extensive experience developing for high/elastic scalable, 24x7x365 high availability digital marketing or e-commerce systems
- Hands-on experience with data computing, storage, and security components and using Cloud Platforms (preferably Google Cloud Platform) provided Big Data technologies
- Hands-on experience with real-time streaming processing as well as high volume batch processing, and skilled in Advanced SQL, Google Cloud Platform BigQuery, Apache Kafka, Data-Lakes, etc.
- Hands-on Experience in Big Data technologies - Hadoop, Hive, and Spark, and an enterprise-scale Customer Data Platform (CDP)
- Experience in at least one programming language (Python strongly preferred), cloud computing platforms (e.g., Google Cloud Platform), big data tools such as Spark/PySpark, columnar datastores (BigQuery preferred), DevOps processes/tooling (CI/CD, GitHub Actions), infrastructure as code frameworks (Terraform), BI Tools (e.g. DOMO, Tableau, Looker,), pipeline orchestration (eg. Airflow)
- Fluency in data science/machine learning basics (model types, data prep, training process, etc.)
- Experience using version control systems (Git is strongly preferred)
- Experience with data governance and data security
- Strong analytical, problem solving and interpersonal skills, a hunger to learn, and the ability to operate in a self-guided manner in a fast-paced rapidly changing environment
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