Senior Data Engineer
Raas Infotek LLC
San Francisco, CA, United States
3 days ago
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Role details
Contract type
Contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source
Tech stack
Airflow
Amazon Web Services
Microsoft Azure
Big Data
BigQuery
Cloud Computing
Continuous Integration
Data Validation
Information Engineering
Data Governance
Data Integration
Extract Transform Load (ETL)
+21 more
Data Systems
Data Warehousing
DevOps
Distributed Computing Environment
Python (Programming Language)
Performance Tuning
SQL Databases
Talend
Google Cloud
Azure Data Factory
Snowflake
Apache Spark
Git
Data Lakes
Pyspark
AWS Glue
Apache Kafka
Data Management
Stream Processing
Data Pipelines
Databricks
Job description
We are seeking an experienced Senior Data Engineer with 10+ years of experience in designing, developing, and maintaining scalable data pipelines and data platforms. The ideal candidate should have strong expertise in ETL/ELT development, cloud technologies, data warehousing, and big data processing., * Design, develop, and maintain scalable ETL/ELT data pipelines.
- Build and optimize data integration and transformation workflows.
- Work with large datasets using SQL, Python, and PySpark.
- Develop and manage data solutions using AWS, Azure, or Google Cloud Platform.
- Implement data warehouses, data lakes, and lakehouse architectures.
- Perform data modeling, data validation, and performance tuning.
- Collaborate with data analysts, architects, and business stakeholders.
- Ensure data quality, security, governance, and pipeline reliability.
Requirements
- 10+ years of experience in Data Engineering.
- Strong expertise in SQL, Python, and PySpark.
- Hands-on experience with ETL tools such as Informatica, Talend, or AWS Glue.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Strong knowledge of Snowflake, Databricks, BigQuery, or Redshift.
- Experience with Apache Spark, Kafka, and distributed data processing.
- Good understanding of data warehousing and data modeling concepts.
- Excellent problem-solving and communication skills., * Experience with CI/CD, Git, and DevOps practices.
- Knowledge of Airflow, Azure Data Factory, or similar orchestration tools.
- Experience with real-time data processing and data governance.
- Ability to lead technical discussions and mentor junior developers.
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