Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - 12 Month(s)
Skills
bigquery
Google Cloud Platform
Extract
Transform
Load
Snow Flake Schema
Privacy
Problem Solving
SQL
Google Cloud
ELT
Job Details
About the Role:
- We are looking for a skilled Data Engineer or Data Analyst with strong expertise in Google BigQuery to join our growing data team. In this role, you will be responsible for managing large-scale data pipelines, optimizing query performance, and enabling data-driven decision-making through scalable solutions built on Google Cloud Platform (Google Cloud Platform).
Key Responsibilities:
- Design, build, and maintain scalable and efficient data pipelines using BigQuery.
- Write complex and optimized SQL queries for data extraction, transformation, and reporting.
- Work with stakeholders to define data requirements and deliver clean, well-documented datasets.
- Develop and maintain data models, materialized views, and partitioned tables in BigQuery.
- Collaborate with data analysts, engineers, and business teams to support advanced analytics and BI dashboards.
- Monitor and improve query performance, data latency, and cost optimization in BigQuery.
- Ensure compliance with data governance, security, and privacy standards.
- Automate data ingestion from external sources via Google Cloud Platform services such as Cloud Storage, Cloud Functions, or Pub/Sub.
Requirements:
- 5+ years of experience working with Google BigQuery in a data engineering or analytics role.
- Proficient in SQL with the ability to write complex queries and optimize performance.
- Experience with ETL/ELT pipelines and cloud data workflows.
- Familiarity with Google Cloud Platform tools like Cloud Composer (Airflow), Dataflow, or Cloud Functions.
- Understanding of data modeling techniques (star schema, snowflake, normalized/denormalized models).
- Comfortable working with large, complex datasets and optimizing storage and compute costs.
- Strong problem-solving and communication skills.
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