Want to hire Lakehouse developer? Then you should know!
How and where is Lakehouse used?
- Real-time Analytics: Processing and analyzing data in real-time to make immediate decisions.
- Data Warehousing: Storing large volumes of structured and unstructured data for analysis.
- Machine Learning: Using algorithms to learn from data and make predictions or decisions.
- Data Exploration: Investigating data to discover patterns, trends, and insights.
- IoT Data Management: Handling massive amounts of data generated by Internet of Things devices.
- Customer Behavior Analysis: Analyzing customer interactions and behaviors to improve products and services.
- Fraud Detection: Identifying and preventing fraudulent activities using data analysis.
- Personalized Marketing: Tailoring marketing strategies based on individual customer preferences.
- Risk Management: Assessing and mitigating risks by analyzing historical and real-time data.
- Supply Chain Optimization: Streamlining supply chain operations using data-driven insights.
Compare Junior, Middle, Senior, and Expert/Team Lead Lakehouse Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 1-3 years |
| 50,000 |
Middle | 3-5 years |
| 70,000 |
Senior | 5-8 years |
| 90,000 |
Expert/Team Lead | 8+ years |
| 120,000 |
Quick Facts about Lakehouse.
- Lakehouse Software Development was born in the magical year of 2019.
- The Lakehouse technology is famous for hosting data lakes and warehouses.
- To dive into Lakehouse, you need a solid background in data engineering.
- Spark, the mighty processing engine, is Lakehouse’s best buddy.
- Did you know? Lakehouse is like having a cabin in the woods for your data!
TOP Lakehouse Related Technologies
- Delta Lake
- Apache Spark
- AWS Glue
- Databricks
- Apache Hudi
What are top Lakehouse instruments and tools?
- Delta Lake: Open-source storage layer that brings ACID transactions to Apache Spark and big data workloads, released by Databricks in 2017
- Apache Hudi: Data lake framework for stream processing on top of Apache Hadoop, originated from Uber in 2019
- Snowflake Data Lake: Cloud-based data platform that provides a single and integrated platform for data engineering, data lake, data warehousing, and data sharing, released by Snowflake Inc. in 2014
- Amazon S3: Object storage service offered by Amazon Web Services for storing and retrieving any amount of data, launched in 2006
- Google Cloud Storage: Unified object storage for developers and enterprises, provided by Google Cloud and introduced in 2010
Talk to Our Talent Expert
Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Maria Lapko
Global Partnership Manager