A global financial-services organization is seeking an early-career Data Engineer to join a team building and expanding a modern enterprise data platform. This is an excellent opportunity for a new graduate or engineer with up to two years of experience who wants hands-on exposure to Python, SQL, PySpark, Databricks, and cloud-based data engineering. You will help onboard data into a production data platform, develop ingestion and transformation processes, validate data quality, troubleshoot pipeline issues, and collaborate with teams across the organization. You will work alongside experienced engineers while learning modern data-mesh and lakehouse patterns in a large enterprise environment. RESPONSIBILITIES Build and maintain data-ingestion processes for enterprise datasets.Write Python, PySpark, and SQL for data-processing and transformation tasks.Assist with cleansing, validation, reconciliation, and schema enforcement.Support data pipelines across layered data environments.Monitor scheduled workflows and help investigate pipeline failures.Collaborate with technical and business teams onboarding data onto the platform.Document pipeline logic, transformations, technical decisions, and fixes.Participate in code reviews, testing, version control, and deployment processes. Role Requirements: 0 to 2 years of experience in data engineering, software development, analytics engineering, or a related area. Internships and academic projects count.Bachelor's degree in Computer Science, Engineering, Information Systems, or a related discipline.Foundational SQL skills including joins, aggregations, and filtering.Hands-on Python programming ability.Basic understanding of object-oriented programming.Strong understanding of tables, schemas, relational data, and data transformations.Exposure to Spark, PySpark, or similar distributed-data technologies.Interest in learning Databricks and modern cloud-data platforms.Strong problem-solving and attention to detail.Ability to communicate clearly and collaborate across teams. PREFERRED EXPERIENCE Databricks experience, coursework, or certification.Familiarity with medallion architecture or Delta Lake.Azure, AWS, or GCP experience.Financial-services exposure.Experience or personal projects involving AI or agentic-AI technologies.