Data Engineer with Databricks, SQL Location: Bellevue, WA/Frisco, TX

Title: Data Engineer with Databricks, SQL

Location: Bellevue, WA/Frisco, TX

(Hybrid – 3 days/week)

Long Term Contract

Google Meta Amazon Apple Netflix Microsoft Nvidia Salesforce Oracle IBM Client Cisco Adobe Palantir Snowflake Databricks Twitter / X LinkedIn Uber Airbnb

Rate is Open ( Since we are looking for Top Tier and Product Background)

Location : First Preference – Bellevue & Frisco TX

Targeted Big Tech / FAANG+ Companies 

Bellevue : Amazon

•   Microsoft ,Google ,Meta ,Apple ,Netflix ,TikTok (ByteDance) ,Snap Inc ,Salesforce ,Oracle ,Adobe ,NVIDIA

Digital Companies 

•   Expedia Group ,Zillowv,Redfin ,Remitly ,OfferUp ,Postmates ,Chewy ,eBay ,Twitch Pinterest

 Texas : 

Amazon ,Google ,Microsoft ,Meta ,Oracle ,Salesforce ,IBM ,Cisco ,NVIDIA ,Client

Digital – CDP .

Match Group Toyota Connected, Southwest Airlines ,American Airlines

McKesson ,7-Eleven ,Pizza Hut ,Raising Cane's ,Dave & Buster's

Product & Fin

ServiceNow ,Salesforce ,Workday ,Intuit

Must Skills:

• Microsoft Fabric (hands-on exposure)
• Azure Data Lake Storage (ADLS)
• Dimensional Modeling (Star Schema)
• Power BI / DAX
• Medallion Architecture (Bronze/Silver/Gold)
• AI tools / automation in data engineering
• Scala / advanced Python scripting
• Databricks
• SQL
• Python
• ETL

Skill Breakdown:

• Skill 1: 7+ Years – Data Engineering, Databricks, SQL, Python
• Skill 2: 7+ Years – SQL, Microsoft Fabric, Azure Data Factory
• Skill 3: 5+ Years – Overall IT Experience

Role Overview:

• Build, maintain, and optimize scalable data pipelines
• Develop data models and analytics layers for reporting
• Modernize legacy pipelines using standardized architecture
• Collaborate with business stakeholders for requirement gathering
• Perform root cause analysis and data validation
• Improve system efficiency, reusability, and performance
• Leverage AI tools to enhance engineering productivity

Technical Expectations:

• Strong SQL (performance tuning & optimization)
• Experience with Databricks, Azure Data Stack, ADLS
• Knowledge of Data Warehousing & Data Lake concepts
• Understanding of dimensional modeling & semantic layers
• Familiarity with Python/Scala for pipeline development
• Exposure to Power BI and downstream analytics

Experience Required:

• 2–4 years of Data Engineering experience
• Hands-on experience with cloud-based data platforms
• Experience in data pipeline design and troubleshooting
• Strong stakeholder communication skills