Title: Databricks Engineer - Remote
Mandatory skills:
operating solutions, Databricks,
ETL, ELT architectures, data ingestion patterns,
Python, Spark, data processing,
dimensional data models, data lakehouse,
AI-driven analytics platforms, semantic modeling, NLP techniques,
data governance, data security, data-driven solutions, data technologies, data models data structures, data pipelines, data quality,
SAFe Agile, reliable analytics solutions, SQL queries, notebooks, data ingestion, transformation,
data cleansing processes, emerging data engineering
Description:
Databricks Engineer
The Person
You are a detail-oriented and analytical problem solver who enjoys tackling complex data challenges. You communicate clearly and collaborate effectively with cross-functional teams to deliver meaningful, data-driven solutions. You are adaptable, service oriented, curious, and passionate about using modern data technologies to unlock insights. Highly organized and proactive, you can manage multiple priorities while maintaining a strong focus on quality, scalability, and innovation.
Key Responsibilities
Implement and optimize data models and structures within Databricks to support efficient querying, analytics, and reporting.
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows, with a strong emphasis on dimensional data modeling and data quality.
Partner with engineering teams and business stakeholders to gather requirements and deliver reliable analytics solutions.
Develop, optimize, and maintain SQL queries, notebooks, and scripts for data ingestion, transformation, and processing.
Ensure data accuracy, consistency, and integrity through validation, monitoring, and data cleansing processes.
Create and maintain comprehensive documentation for data pipelines, models, and analytics solutions.
Monitor, troubleshoot, and optimize data pipelines and analytics workloads to ensure performance and reliability.
Stay current with industry trends, including AI-driven analytics tools, semantic modeling, and emerging data engineering best practices.
Preferred Experience
Hands-on experience implementing and operating solutions in Databricks.
Strong understanding of ETL/ELT architectures and data ingestion patterns.
Proficiency in Python and/or Spark for large-scale data processing.
Experience designing and implementing dimensional data models in data lakehouse environments.
Familiarity with AI-driven analytics platforms, semantic modeling concepts, and NLP techniques.
Experience working in SAFe Agile or other scaled Agile environments.
Solid understanding of data governance, security, and compliance best practices in global environments with numerous data providers and consumers.
Academic Credentials
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field preferred.
Master’s degree is a plus.
Databricks and Azure certifications strongly preferred.
Notes:
Remote
40 hours per week (no overtime)
VIVA USA is an equal opportunity employer and is committed to maintaining a professional working environment that is free from discrimination and unlawful harassment. The Management, contractors, and staff of VIVA USA shall respect others without regard to race, sex, religion, age, color, creed, national or ethnic origin, physical, mental or sensory disability, marital status, sexual orientation, or status as a Vietnam-era, recently separated veteran, Active war time or campaign badge veteran, Armed forces service medal veteran, or disabled veteran. Please contact us at for any complaints, comments and suggestions.
Contact Details :
Account co-ordinator: Sekhar Radhakrishnan
VIVA USA INC.
3601 Algonquin Road, Suite 425
Rolling Meadows, IL 60008
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