PLANIT Group
Washington, DC Contract On-Site Flexibility/Remote:
Seeking a highly skilled and motivated Data Engineer to join our dynamic team. As a Data Engineer, you will play a crucial role in designing, developing, and maintaining our data infrastructure. Your expertise in Python, PySpark, ETL processes, CI/CD (Jenkins or GitHub), and experience with both streaming and batch workflows will be essential in ensuring the efficient flow and processing of data to support our clients.
Responsibilities: Data Architecture and Design:
Collaborate with cross-functional teams to understand data requirements and design robust data architecture solutions. Develop data models and schema designs to optimize data storage and retrieval. ETL Development:
Implement ETL processes to extract, transform, and load data from various sources. Ensure data quality, integrity, and consistency throughout the ETL pipeline. Python and PySpark Development:
Utilize your expertise in Python and PySpark to develop efficient data processing and analysis scripts. Optimize code for performance and scalability, keeping up-to-date with the latest industry best practices. Data Integration:
Integrate data from different systems and sources to provide a unified view for analytical purposes. Collaborate with data scientists and analysts to implement solutions that meet their data integration needs. Streaming and Batch Workflows:
Design and implement streaming workflows using PySpark Streaming or other relevant technologies. Develop batch processing workflows for large-scale data processing and analysis. CI/CD Implementation:
Implement and maintain continuous integration and continuous deployment (CI/CD) pipelines using Jenkins or GitHub Actions. Automate testing, code deployment, and monitoring processes to ensure the reliability of data pipelines.
Qualifications:
Bachelor's or master's degree in computer science, Information Technology, or a related field. 7+ years of proven experience as a Data Engineer or similar role. Strong programming skills in Python and expertise in PySpark for both batch and streaming data processing. Hands-on experience with ETL tools and processes. Familiarity with CI/CD tools such as Jenkins or GitHub Actions. Solid understanding of data modeling, database design, and data warehousing concepts. Excellent problem-solving and analytical skills. Strong communication and collaboration skills.
Preferred Skills:
Knowledge of cloud platforms such as AWS, Azure, or Google Cloud. Experience with version control systems (e.g., Git).
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Responsibilities: Data Architecture and Design:
Collaborate with cross-functional teams to understand data requirements and design robust data architecture solutions. Develop data models and schema designs to optimize data storage and retrieval. ETL Development:
Implement ETL processes to extract, transform, and load data from various sources. Ensure data quality, integrity, and consistency throughout the ETL pipeline. Python and PySpark Development:
Utilize your expertise in Python and PySpark to develop efficient data processing and analysis scripts. Optimize code for performance and scalability, keeping up-to-date with the latest industry best practices. Data Integration:
Integrate data from different systems and sources to provide a unified view for analytical purposes. Collaborate with data scientists and analysts to implement solutions that meet their data integration needs. Streaming and Batch Workflows:
Design and implement streaming workflows using PySpark Streaming or other relevant technologies. Develop batch processing workflows for large-scale data processing and analysis. CI/CD Implementation:
Implement and maintain continuous integration and continuous deployment (CI/CD) pipelines using Jenkins or GitHub Actions. Automate testing, code deployment, and monitoring processes to ensure the reliability of data pipelines.
Qualifications:
Bachelor's or master's degree in computer science, Information Technology, or a related field. 7+ years of proven experience as a Data Engineer or similar role. Strong programming skills in Python and expertise in PySpark for both batch and streaming data processing. Hands-on experience with ETL tools and processes. Familiarity with CI/CD tools such as Jenkins or GitHub Actions. Solid understanding of data modeling, database design, and data warehousing concepts. Excellent problem-solving and analytical skills. Strong communication and collaboration skills.
Preferred Skills:
Knowledge of cloud platforms such as AWS, Azure, or Google Cloud. Experience with version control systems (e.g., Git).
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