Job Description: We are seeking a Data Engineer with a minimum of 4 years of hands-on experience in building scalable and efficient data pipelines using modern big data technologies and cloud platforms. This individual will work on end-to-end data engineering tasks—from data modeling and pipeline development to orchestration and automation—supporting key analytics and business intelligence functions. Key Responsibilities: • Design, model, and build robust data pipelines using big-data technologies such as Hadoop, Hive, PySpark, and Python • Integrate and manage data in Amazon AWS S3 – focusing on object storage, security, and data service integrations • Apply business logic to raw data to transform it into consumable formats for downstream systems and analytics • Automate pipeline processes and ETL workflows using Spark, Python, and Hive • Manage and schedule batch jobs using Autosys • Build and maintain data models and data marts with sound database design principles (MySQL or equivalent) • Develop dashboards and reports using PowerBI and Dremio • Perform scripting and automation tasks using UNIX/Shell scripting • Participate in CI/CD practices to streamline development and deployment • Troubleshoot and resolve data-related issues proactively • Collaborate with cross-functional teams to gather requirements and deliver data solutions Required Qualifications: • Minimum 4 years of professional experience in data engineering roles • Strong hands-on experience with: • Hadoop, Hive, PySpark, Python • AWS S3 – storage, security, and data integration • Autosys – job scheduling and orchestration • PowerBI, Dremio – reporting and visualization • Unix/Shell scripting, CI/CD pipelines • Solid understanding of data modeling and database design • Proven ability to work independently and take ownership of deliverables EEO: “Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.”