Data Engineer (Python/PySpark/Spark)

Role Overview We are 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 clients' data infrastructure. Your expertise in Apache Spark, 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 robust ETL processes to extract, transform, and load data from various sources. Ensure data quality, integrity, and consistency throughout the ETL pipeline. Distributed Computing & Spark Development: Utilize your expertise in Apache Spark, Python, and PySpark to develop efficient, large-scale data processing and analysis scripts. Optimize code for performance, memory management, 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. Proven experience as a Data Engineer or similar role. Strong programming skills in Python and deep expertise in Apache Spark and PySpark for both batch and streaming data processing. Hands‑on experience developing, tuning, and troubleshooting distributed data pipelines. Solid understanding of ETL tools, data modeling, database design, and data warehousing concepts. Familiarity with CI/CD tools such as Jenkins or GitHub Actions. Excellent problem‑solving, analytical, communication, and collaboration skills. Preferred Skills Experience with Ab Initio (e.g., GDE, Co‑Operating System, EME) or a strong background in enterprise ETL modernization. Knowledge of cloud platforms such as AWS, Azure, or Google Cloud. Experience with version control systems (e.g., Git). Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes). Understanding of data security and privacy best practices. Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. #J-18808-Ljbffr Infinitive