[Remote] Senior/Principal Engineers: Data Engineers & Data Scientists
Note: The job is a remote job and is open to candidates in USA. BRK Tech, a Berkshire Hathaway Group Company, partners across various businesses to build modern, scalable data and AI platforms. They are seeking Senior and Principal-level Data Engineers, Data Scientists, and AI/ML Engineers to drive large-scale data systems and advanced analytics initiatives.
Responsibilities
- Engineers in this track design and operate scalable data platforms and pipelines supporting enterprise analytics and AI
- This track focuses on building and productionizing statistical models and machine learning systems to solve complex real-world problems
- This track focuses on building high-quality data models, reporting layers, and analytics platforms for enterprise decision-making
Skills
- Bachelor's degree or equivalent practical experience (4+ additional years)
- Typically 6–8+ years with strong hands‑on technical ownership for Senior Engineers
- Typically 10+ years with deep expertise, system design ownership, and cross‑team influence for Principal Engineers / Leads
- 8+ years of experience (10+ for Principal) in data engineering
- Strong programming in Python, Spark, and SQL
- Experience with high‑volume, operational data systems
- Deep expertise in ETL/ELT pipelines, data modeling, and performance tuning
- Hands‑on experience with Azure Data Factory, Azure Databricks, or similar platforms
- Building and maintaining enterprise‑scale data architectures
- Experience across the full data lifecycle: design, development, optimization, and operations
- Data security, reliability, and governance principles
- Exposure to modern data platforms and distributed processing
- 8+ years of experience (10+ for Principal) in data science or applied ML
- Strong programming in Python and/or R
- Hands‑on experience with SQL, PySpark, and large‑scale datasets
- Expertise in at least one domain: Machine learning (supervised/unsupervised), Time‑series forecasting, Statistical modeling or survival analysis
- Experience with libraries such as scikit‑learn, pandas, tidyverse
- Strong foundation in statistics (hypothesis testing, inference, correlation)
- Experience building and validating models across multiple data sources (APIs, databases, data lakes)
- Proven ability to productionize ML models from development to deployment
- Data visualization experience (Power BI or similar)
- Ability to translate complex problems into analytical and technical solutions
- 6+ years of experience in data, BI, or analytics engineering
- Expert‑level SQL, data modeling, and performance optimization
- Deep understanding of data warehousing and semantic layer design
- Experience building ETL pipelines and reporting systems
- Strong experience with large‑scale, enterprise data integration
- Building fault‑tolerant, highly available analytics systems
- Experience with data visualization and reporting platforms
- Ability to translate business requirements into scalable data models
- Strong understanding of deployment architectures and system design
- Experience operating in shared code ownership environments
- Deep expertise across data architecture, analytics, or AI platforms
- Proven ability to drive large‑scale technical initiatives end‑to‑end
- Strong experience influencing cross‑functional stakeholders
- Ability to evaluate and evolve data and AI platform strategy
- Expertise in modern data ecosystems (cloud, open‑source, or hybrid)
- Strong communication skills to bridge business and engineering
- Experience setting best practices across architecture, scalability, and performance
- Modernization from legacy BI to cloud data platforms (Azure, Databricks)
- Exposure to distributed data systems and real‑time analytics
Company Overview