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Bayrock Labs

Principal Data Engineer

  • Seen live on Bayrock Labs' site 3 days ago
  • Senior
Pay
$80 to $85 an hour USD
Location
Milpitas, CA
Open for
13+ days
First seen
Oct 22, 2026
Apply on Bayrock Labs' site (opens in a new tab)

Posting record

No flags

Open 13+ days

The posting's record, oldest first
  1. Bayrock Labs' site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Bayrock Labs, so its true age is longer.

Last checked Nov 1, 2026.

How well do you match?

See how much of this posting your resume shows, and what it's missing.

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What the posting discloses

Pay
$80 to $85 an hour USD

Not stated: Real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Skills mentioned

About the role

About BayRock Labs

At BayRock Labs, we pioneer innovative tech solutions that drive business transformation. As a leading product engineering firm based in Silicon Valley, we provide full-cycle product development, leveraging cutting-edge technologies in AI, ML, and data analytics. Our collaborative, inclusive culture fosters professional growth and work-life balance. Join us to work on ground-breaking projects and be part of a team that values excellence, integrity, and innovation. Together, let's redefine what's possible in technology.

We are looking for a highly skilled Senior Data Engineer / Data Architect with deep hands‑on expertise in Azure, Databricks, PySpark, Python, SQL, and modern data warehousing . This role is ideal for someone who has built large‑scale data platforms, designed enterprise‑grade architectures, and delivered high‑quality data products in cloud environments.

Core Technical Expertise

Azure Cloud Platform

  • ADLS Gen2, ADF, Synapse, Azure SQL, Key Vault, App Services
  • Cloud‑native architecture design, scalability, and cost optimization
  • Security & governance: RBAC, Managed Identity, Private Endpoints

Databricks Engineering

  • End‑to‑end development on Azure Databricks
  • Lakehouse architecture implementation
  • Delta Live Tables (DLT), Unity Catalog
  • Performance tuning, cluster optimization
  • CI/CD for Databricks workloads

Big Data & Processing Frameworks

  • Apache Spark with advanced PySpark transformations
  • Structured Streaming & batch data pipelines
  • Delta Lake architecture & optimization

Programming & Querying

  • Python for automation, data engineering, and orchestration
  • PySpark for distributed data processing
  • SQL for complex query optimization and analytics engineering

Data Architecture & Engineering

  • Enterprise Data Warehouse (EDW) architecture
  • Dimensional modeling (Star/Snowflake)
  • Data Vault 2.0 modeling
  • Metadata‑driven ingestion frameworks
  • Change Data Capture (CDC) implementation
  • Medallion architecture (Bronze/Silver/Gold)
  • Data lineage, governance, cataloging
  • Master Data Management (MDM)

Data Products & Analytics Enablement

  • Design and delivery of scalable data products
  • Business‑aligned semantic layer design
  • KPI frameworks & enterprise reporting enablement
  • Integration of ERP, SaaS, and operational systems
  • Hybrid Lakehouse + EDW architectures

DevOps & Engineering Practices

  • CI/CD pipelines (Azure DevOps, GitHub Actions, Bitbucket)
  • Infrastructure as Code (Terraform, ARM templates)
  • Automated testing (unit, integration, data quality)
  • Monitoring, logging, and observability
  • Agile/Scrum delivery

Strategic & Leadership Impact

  • Principal‑level solution architecture design
  • Cross‑functional stakeholder collaboration
  • Technical roadmap planning and execution
  • Guidance on data governance frameworks (GDPR, SOX)
  • Cloud cost optimization strategies
  • Migration from legacy EDWs (Teradata, Oracle, SQL Server) to Lakehouse

Ideal Candidate Profile

  • 5–10+ years of hands‑on experience in data engineering or data architecture
  • Strong expertise in Azure + Databricks ecosystem
  • Proven experience building scalable, secure, high‑performance data platforms
  • Ability to lead design discussions, influence architecture decisions, and mentor teams
  • Strong problem‑solving mindset and passion for modern data engineering

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