Senior Data Engineer
Centillion Infotech
Glendale, CA, United States
24 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
9 years minimum
Working hours
Regular working hours
Job source
Tech stack
Agile Methodology
Amazon Web Services
Data Analysis
Microsoft Azure
Big Data
BigQuery
Cloud Computing
Code Review
Computer Programming
Databases
Continuous Integration
Data Architecture
+29 more
Information Engineering
Data Governance
Extract Transform Load (ETL)
Data Systems
Data Warehousing
DevOps
Distributed Computing Environment
Apache Hadoop
Python (Programming Language)
Meta-Data Management
Scrum Methodology
Standard Sql
SQL Databases
Enterprise Data Management
Data Processing
Google Cloud
Real Time Systems
Azure Data Factory
Snowflake
Apache Spark
Git
Data Lakes
Information Technology
AWS Glue
Integration Frameworks
Apache Kafka
Data Management
Data Pipelines
Databricks
Job description
We are seeking an experienced Senior Data Engineer to design, develop, and optimize scalable data solutions that support business intelligence, analytics, and enterprise data initiatives. The ideal candidate will have strong expertise in data engineering, cloud platforms, ETL/ELT pipelines, data modeling, and big data technologies. This role requires collaboration with data analysts, architects, business teams, and engineering teams to deliver reliable and high-performance data solutions. Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
- Build and optimize data platforms, data warehouses, and data lakes.
- Develop data integration solutions using batch and real-time processing frameworks.
- Perform data modeling, transformation, cleansing, and validation activities.
- Collaborate with business stakeholders and data analysts to understand data requirements.
- Implement solutions using cloud-based data technologies and modern data architectures.
- Optimize SQL queries, data processing jobs, and system performance.
- Ensure data quality, security, governance, and compliance standards.
- Troubleshoot complex data issues and provide root cause analysis.
- Develop and maintain technical documentation for data solutions.
- Participate in Agile ceremonies, design discussions, and code reviews.
- Mentor junior engineers and contribute to best practices within the data engineering team.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
- 9-13 years of experience in Data Engineering, ETL development, and enterprise data solutions.
- Strong programming experience with Python, SQL, and data processing frameworks.
- Hands-on experience designing and developing ETL/ELT pipelines.
- Strong experience with data warehousing concepts, data modeling, and database technologies.
- Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
- Experience with big data technologies and distributed processing systems.
- Strong analytical, problem-solving, and communication skills.
Preferred Skills
- Experience with Apache Spark, Hadoop, Kafka, Databricks, or Snowflake.
- Experience with cloud data services such as AWS Glue, Azure Data Factory, BigQuery, or similar platforms.
- Knowledge of data lake, lakehouse, and modern data architecture patterns.
- Experience with CI/CD, DevOps practices, and automation.
- Familiarity with data governance, metadata management, and data quality frameworks.
- Experience working in Agile/Scrum environments.
Technical Skills
- Python
- SQL
- ETL / ELT Development
- Data Warehousing
- Data Modeling
- Data Lakes
- Apache Spark
- Databricks
- Snowflake
- Hadoop
- Kafka
- Cloud Platforms (AWS/Azure/GCP)
- Azure Data Factory / AWS Glue
- Database Technologies
- API Integration
- Git
- CI/CD Pipelines
- Agile/Scrum
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