About Infosys Infosys is a global leader in next‑generation digital services and consulting. We enable clients in more than 56 countries to navigate their digital transformation. With over four decades of experience, we help enterprises through their digital journey using an AI‑powered core and agile digital at scale to deliver unprecedented performance and customer satisfaction. Infosys is recognized as the #1 Top Employer in Australia for the second year in a row. Role Description Senior Data Engineer – Sydney, AustraliaAnnual gross salary: AUD 108,571 – 119,893. Flexible working arrangements (hybrid, reviewed case‑by‑case). Please note the salary range is indicative and may be subject to enhancements based on internal processes. Roles and Responsibilities Enhance, optimize, and maintain existing data ingestion, transformation, and extraction pipelines for reporting and analytics on the Unified Data platform. Work with Product Owner and Chapter Lead to understand quarterly priorities and OKRs, gathering detailed requirements for planned Epics. Perform data wrangling, profiling, and analysis for new and derived datasets using on‑premises and cloud‑native tools. Coordinate with other teams for planning, design, governance, engineering, and release management to ensure timely and accurate delivery of data and services. Build new data assets and pipelines tailored to downstream requirements (e.g., datasets for Tableau or TM1 cubes). Document low‑level design, source‑to‑column mapping, test cases, production release implementation plans, and operational support manuals. Schedule data pipelines using Control‑M and Airflow, ensuring correct upstream dependencies and SLA compliance. Provide warranty support to Operations post‑production release and update documentation accordingly. Collaborate with multiple business and IT teams to deliver the final outcome. Ensure effective communication and collaboration across multiple stakeholders and business units. Gain functional knowledge by reviewing existing code to understand the domain. Adapt to an agile environment with constant change and diverse challenges. Work effectively within tight timeframes, balancing the needs of multiple stakeholders and managing competing priorities. Key Skills & Competencies Essential Education: Bachelor’s, Master’s, or Doctorate in Mathematics, Statistics, Computer Science, or Information Management. Work Experience: 8+ years in Data Engineering and Data Warehousing. Technical Skills: Design, build, and optimize scalable pipelines using Azure Databricks, PySpark, and Delta Lake; develop complex SQL and Python for large‑scale data transformation; strong hands‑on experience with Azure Databricks, Delta Lake, and Azure data services (ADLS, ADF); proficiency in Python, PySpark, CI/CD, and SQL; familiarity with CI/CD tools (BitBucket/GitHub, Jenkins, Nexus); ability to manage structured and unstructured data. Preferred Experience working with distributed data engineering teams. Excellent communication and stakeholder management skills. Strong prioritization and pragmatic problem‑solving abilities. Additional Customer‑facing and written communication skills. Attention to detail and strong analytical skills. Proficiency in Excel, Word, and PowerPoint. Capacity to prioritize and manage concurrent activities. Benefits Income Protection Insurance Paid Parental and Volunteer leaves Employee Assistance Program (EAP) Flexible working arrangements Health Insurance Discount and Well‑being Program Access to Fitness and Gym Memberships Salary packaging and novated leasing Equal Opportunity Statement All aspects of employment at Infosys are based on merit, competence and performance. Infosys embraces diversity and creates an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer. #J-18808-Ljbffr