Want to hire Data Lake developer? Then you should know!
How and where is Data Lake used?
- Data Storage: Storing vast amounts of data
- Data Analytics: Analyzing large datasets
- Data Integration: Combining data from various sources
- Machine Learning: Training models on big data
- Real-time Processing: Processing data in real-time
- Data Exploration: Exploring data for insights
- Data Archiving: Archiving historical data
- Data Backup: Backing up critical data
- Data Security: Securing sensitive data
- Data Governance: Ensuring data compliance
Compare Junior, Middle, Senior, and Expert/Team Lead Data Lake Developer roles
Seniority Name | Years of experience | Responsibilities and activities | Average salary (USD/year) |
---|---|---|---|
Junior | 1-3 years |
| 50,000 |
Middle | 3-5 years |
| 75,000 |
Senior | 5-8 years |
| 100,000 |
Expert/Team Lead | 8+ years |
| 150,000 |
Quick Facts about Data Lake.
- Data Lake Software Development was born in 2010.
- The most popular project types include big data analytics.
- The entry threshold for this technology is understanding data architecture.
- Hadoop is the most popular related technology in this field.
- Fun Fact: Data lakes can store massive amounts of unstructured data.
TOP Data Lake Related Technologies
- Apache Hadoop
- Amazon S3
- Google Cloud Storage
- Microsoft Azure Data Lake Storage
- Snowflake
- Apache Spark
- IBM Cloud Object Storage
- Databricks
- AWS Glue
- Talend
What are top Data Lake instruments and tools?
- Hadoop: The big elephant in the room by Apache, released in 2011.
- AWS Glue: Amazon’s data prep and integration tool since 2016.
- Azure Data Lake: Microsoft’s offering from 2016 for big data.
- Google Cloud Dataflow: Data processing by Google since 2014.
- Cloudera: The data management platform since 2008.
Talk to Our Talent Expert
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Maria Lapko
Global Partnership Manager