Data Engineer

We are seeking a skilled and motivated Data Engineer with 3-4 years of experience to join our growing data team. The ideal candidate will have a strong foundation in data pipeline architecture, ETL/ELT processes, and cloud data platforms, along with a passion for building scalable, reliable, and high-performance data systems. Responsibilities: Design, build, and maintain scalable data pipelines for both batch and real-time processing. Develop ETL/ELT workflows to ingest, transform, and deliver high-quality data from diverse sources. Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable, well-structured datasets. Ensure data quality, integrity, and governance across the pipeline lifecycle. Optimize data systems for performance, scalability, and cost-efficiency. Implement and manage cloud data infrastructure (AWS, GCP, or Azure). Monitor, debug, and troubleshoot issues in data workflows and pipelines. Requirements: Bachelor's degree in Computer Science, Engineering, or related field. 3-4 years of professional experience as a Data Engineer. Strong programming skills in Python, SQL, and at least one scripting language. Hands-on experience with cloud platforms such as AWS (S3 Glue, Redshift), GCP (BigQuery, Dataflow), and Azure (Data Lake, Synapse). Practical knowledge of data pipeline tools like Apache Airflow, dbt, Kafka, or similar. Proficiency in relational and NoSQL database design and optimization. Solid understanding of data warehousing concepts and data modeling. Experience working with Jupyter Notebook and data analysis libraries such as Pandas. Familiarity with Git, CI/CD pipelines, and DevOps practices. Preferred / Bonus Skills: Experience with PySpark or other distributed data processing frameworks. Exposure to containerization (Docker, Kubernetes) for data applications. Knowledge of data security, privacy, and compliance standards.

#J-18808-Ljbffr