Data Engineer/Data Scientist (Capacity Planning-Forecasting)

Bayside Solutions; Cupertino (CA); Remote; USD 171,924,000 - 200,579,000; Full time

Job summary

Bayside Solutions is seeking a Senior Data Engineer/Data Scientist to lead capacity forecasting, cloud cost modeling, and infrastructure efficiency initiatives. Remote role based in Cupertino, CA, with a W2 contract and pay rate of $60-$70 per hour.

The role combines data engineering, forecasting, and FinOps to enable scalable, cost-efficient infrastructure decisions across Media and its business units. You will own forecasts, develop cost models, and drive cost-optimization initiatives.

Qualifications

• 6+ years of experience in data engineering, analytics, or FinOps.
• Strong Python and SQL for data processing, modeling, and analysis.
• Experience building forecasting models and working with time-series data.

Responsibilities

• Own end-to-end infrastructure demand forecasting across compute, storage, networking, and accelerator resources.
• Develop and maintain 12-15 month forecasts using time-series techniques (ARIMA, Prophet).
• Gather inputs from product and engineering teams and incorporate growth signals.
• Build cost attribution models allocating infrastructure spend across teams, products, and workloads.
• Design dashboards and reporting frameworks for forecast vs. allocation and capacity utilization trends.

Skills

Data engineering

Analytics

FinOps

Python

SQL

Forecasting

Tools

Spark

Tableau

Looker

Job description

Data Engineer/Data Scientist (Capacity Planning-Forecasting)

W2 Contract

Pay Rate: $60 - $70 per hour

Location: Cupertino, CA - Remote Role

Job Summary:

We are seeking a Senior Data Engineer to lead capacity forecasting, cloud cost modeling, and infrastructure efficiency initiatives across Media and its associated business units. This role combines data engineering, forecasting, and FinOps to enable scalable, cost-efficient infrastructure decisions.

Duties and Responsibilities:

• Own end-to-end infrastructure demand forecasting across compute, storage, networking, and accelerator resources.
• Develop and maintain 12-15 month forecasts using time-series techniques (e.g., ARIMA, Prophet).
• Gather and validate inputs from product and engineering teams, incorporating business growth and roadmap signals.
• Track and improve forecast accuracy (actual vs. forecast %) and forecast stability over time.
• Build and maintain cost attribution models that allocate infrastructure spend (compute, accelerators, storage, networking, data transfer) across teams, products, and workloads.
• Develop cost-of-revenue pipelines and reporting models to provide clear visibility into spend drivers.
• Define and monitor unit cost metrics such as cost per request, cost per GB stored, and cost per pipeline execution.
• Analyze infrastructure usage to identify inefficiencies, underutilization, and cost optimization opportunities.
• Drive initiatives including:
  • Rightsizing resources
  • Reserved/committed usage strategies
  • Spot/preemptible workload optimization
• Track utilization, efficiency targets, and cost avoidance metrics.
• Design and build scalable data pipelines and models to process large-scale infrastructure, billing, and usage datasets.
• Enable reliable ingestion, transformation, and serving of data for forecasting and cost analytics.
• Develop self-service datasets and dashboards to support engineering and finance teams.
• Create dashboards and reporting frameworks for:
  • Forecast vs. request vs. allocation
  • Allocation efficiency
  • Capacity utilization trends
• Support scenario analysis (what-if modeling) to guide infrastructure scaling and investment decisions.
• Deliver clear, concise insights to technical and business stakeholders.
• Partner with SRE, infrastructure, product, finance, and procurement teams to align capacity and cost strategies.
• Establish feedback loops to inform:
  • Product roadmap decisions
  • Infrastructure scaling strategies
  • Process and service improvements
• Promote a cost-aware engineering culture through transparency and tooling.

Requirements and Qualifications:

• 6+ years of experience in data engineering, analytics, or FinOps, with exposure to cloud infrastructure or capacity planning.
• Strong proficiency in Python and SQL for data processing, modeling, and analysis.
• Experience building forecasting models and working with time-series data.
• Solid understanding of cloud infrastructure and billing systems (compute, storage, networking, accelerators).
• Experience with cost allocation methodologies and optimization techniques (e.g., reserved instances, committed use discounts, rightsizing).
• Strong analytical skills with the ability to translate complex datasets into actionable insights.
• Ability to operate effectively in ambiguous, fast-paced environments with a bias for action.

Preferred Qualifications

• Experience with large-scale data processing frameworks (e.g., Spark) or cloud data platforms.
• Familiarity with SRE practices and infrastructure monitoring systems.
• Experience building data visualization and reporting solutions (e.g., Tableau, Looker).
• Exposure to FinOps frameworks and governance models.
• Strong written and verbal communication skills with experience presenting to cross-functional stakeholders.

Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate.

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