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Closed on August 12, 2026.
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Data Engineer Hadoop, HIVE & Python
Python
Analytics
Big Data
Bigdata
Business Analytics
Business Intelligence
Data Analytics
Data Architecture
Data Engineer
Data Integration
Data Lake
Data Pipeline
Data Platform
Data Processing
Database
Databases
Databricks
ETL
Hadoop
Hive
Informatica
Reporting and Analytics
Spark
SQL
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Job Description
Compensation and setting: This on-site Data Engineer role in Birmingham, AL offers an hourly rate of USD 58 and the opportunity to design, build, and support data engineering and analytics solutions using a blend of on-premises tools and cloud services. You will work with Hadoop, HIVE, Spark, Python, and related technologies in a collaborative, delivery-focused environment.
Responsibilities
- Design, develop, and support data engineering and analytics solutions across on-premises tools and cloud services.
- Build robust data pipelines to handle both batch and real-time processing.
- Define data models, access patterns, schemas, and storage strategies to meet business needs.
- Implement data quality processes and tooling to ensure reliable analytics.
- Create functional and technical designs for data engineering and analytics projects.
- Model data across diverse schemas and source types to support analytics use cases.
- Develop analytics and AI/ML capabilities using Python and/or R.
- Work with Hadoop, HIVE, and Spark in production environments to drive insights.
- Deliver data sourcing, enrichment, and delivery via APIs and Web Services.
- Collaborate on containerized deployments using Docker and OpenShift.
- Apply Agile and DevOps practices, including CI/CD, to data projects.
- Leverage on-prem MSBI (SSIS/SSAS), Informatica, Oracle GoldenGate, SQL, Oracle, and SQL Server, along with Azure data tools, for end-to-end solutions.
Requirements
- Minimum 3 years of hands-on experience designing, developing, testing, deploying, and supporting data engineering and analytics solutions.
- Experience with batch and real-time data processing frameworks.
- Experience with data modelling, data access, schemas, and data storage techniques.
- Experience with data quality tools.
- Experience creating functional and technical designs for data engineering and analytics solutions.
- Experience implementing data models across diverse schemas and data source types.
- Hands-on experience with Hadoop, HIVE, and Spark.
- Hands-on experience developing and supporting AI/ML solutions using Python and/or R.
- 5+ years hands-on experience designing, developing, testing, deploying, and supporting data engineering and analytics solutions using on-premises tools such as MSBI (SSIS/SSAS), Informatica, Oracle Golden Gate, SQL, Oracle, and SQL Server.
- 3+ years hands-on experience designing, developing, testing, deploying, and supporting data engineering and analytics solutions using Microsoft cloud-based tools such as Azure Data Lake, Azure Data Factory, Azure Databricks, Python, Azure Synapse, Azure Key Vault, and Power BI.
- Experience with containerization methodologies Docker, OpenShift, etc.
- Experience with Agile as well as DevOps and CI/CD methodologies.
- Hands-on experience designing and developing solutions involving data sourcing, enrichment, and delivery using APIs and Web Services.
- Bachelor's degree required.
Technologies
- Hadoop
- HIVE
- Spark
- R
- Python
- MSBI (SSIS/SSAS)
- Informatica
- Oracle GoldenGate
- SQL
- Oracle
- SQL Server
- Azure Data Lake
- Azure Data Factory
- Azure Databricks
- Azure Synapse
- Azure Key Vault
- Power BI
- Docker
- OpenShift
- APIs & Web Services
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