create a job description for data science with data engineering background google stack and big query experience, hybrid position in san francisco, long term contract to hire position, rate $80/hr on 1099 all inclsuvie - San Ramon CA - Fully Onsite

Location: San Ramon, CA
Work Arrangement: Fully Onsite
Job Type: Long-Term Contract-to-Hire
Pay Rate: $120/hour on 1099, all-inclusive

Job Description

We are seeking an experienced Senior Data Scientist / Data Engineer with a strong background in data engineering, machine learning, and cloud-based analytics to join our team in San Ramon, California.

The ideal candidate will have hands-on experience with Google Cloud Platform (Google Cloud Platform), Google BigQuery, Looker, Python, SQL, and machine learning. This role requires a combination of data engineering expertise and data science capabilities, including building scalable data pipelines, developing advanced analytics solutions, creating machine learning models, and delivering actionable business insights.

The successful candidate will work with large and complex datasets, design reliable data processing workflows, optimize data warehouse performance, and develop analytical solutions that support business decision-making. Strong experience with the Google Cloud ecosystem and the ability to translate business requirements into scalable technical solutions are essential.

This is a fully onsite, long-term contract-to-hire opportunity in San Ramon, CA.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Google Cloud Platform.

• Build, optimize, and manage complex SQL queries, tables, views, and analytical datasets in Google BigQuery.

• Develop efficient data models and data transformation processes to support reporting, analytics, and machine learning use cases.

• Build and maintain data integration workflows to ingest, cleanse, transform, and validate data from multiple sources.

• Develop and deploy machine learning models for predictive analytics, forecasting, classification, and other business applications.

• Use Python and relevant data science libraries for data processing, exploratory data analysis, feature engineering, and model development.

• Develop dashboards, reports, and data visualizations using Looker to communicate key metrics and business insights.

• Create and maintain reusable LookML models, semantic layers, and governed data definitions where applicable.

• Optimize BigQuery queries, data structures, and workloads for performance, scalability, and cost efficiency.

• Apply statistical analysis and machine learning techniques to identify patterns, trends, anomalies, and business opportunities.

• Implement data quality checks, pipeline monitoring, validation procedures, and troubleshooting mechanisms.

• Collaborate with data engineers, data scientists, analysts, and business stakeholders to translate requirements into technical solutions.

• Follow best practices for data governance, security, documentation, version control, and production deployment.

• Monitor and improve the reliability, accuracy, and performance of data pipelines, analytical models, and reporting solutions.

Required Qualifications

• Strong professional experience in Data Science and Data Engineering, with the ability to work across both disciplines.

• Hands-on experience with Google Cloud Platform (Google Cloud Platform) and its data analytics ecosystem.

• Strong experience with Google BigQuery, including advanced SQL, query optimization, data modeling, and large-scale analytics.

• Experience developing dashboards, reports, and semantic data models using Looker and/or LookML.

• Strong Python programming skills for data processing, analytics, automation, and machine learning.

• Solid understanding of ETL/ELT pipelines, data integration, data warehousing, and dimensional modeling.

• Experience developing, evaluating, and optimizing machine learning models.

• Knowledge of statistical analysis, exploratory data analysis, feature engineering, and model evaluation techniques.

• Experience working with large, complex datasets and designing scalable data solutions.

• Understanding of data quality, validation, governance, and data security best practices.

• Strong analytical thinking, problem-solving, communication, and collaboration skills.

• Ability to work fully onsite in San Ramon, CA.

Preferred Qualifications

• Experience with Google Cloud Platform data services such as Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.

• Familiarity with Vertex AI or other Google Cloud machine learning services.

• Experience with machine learning libraries and frameworks such as pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.

• Experience with LookML development, Looker explores, dimensions, measures, and governed metrics.

• Familiarity with Apache Airflow, dbt, or other data orchestration and transformation tools.

• Experience deploying and monitoring machine learning models in production environments.

• Knowledge of CI/CD, Git, automated testing, and data pipeline deployment practices.

• Experience working with cross-functional teams to deliver enterprise-level analytics and data science solutions.

Ideal Candidate Profile

The ideal candidate is a hands-on technical professional who combines strong data engineering foundations with practical data science and machine learning experience. They should be comfortable building production-grade data pipelines, working extensively with BigQuery, developing Looker analytics, and applying machine learning techniques to solve business problems.

Candidates with deep expertise in the Google Cloud ecosystem and experience delivering end-to-end data solutions are strongly encouraged to apply.

Position Details

• Role: Senior Data Scientist / Data Engineer

• Location: San Ramon, CA

• Work Model: Fully onsite

• Engagement: Long-term contract-to-hire

• Rate: $120/hour on 1099, all-inclusive