▷ 3 Days Left Data Engineer

Company Description Sia is a next-generation global management consulting group Founded in 1999 we were born digital Today our strategy and management capabilities are augmented by data science enhanced by creativity and driven by responsibility We re optimists for change and we help clients initiate navigate and benefit from transformation We believe optimism is a force multiplier helping clients to mitigate downside and maximize opportunity With expertise across a broad range of sectors and services our 3 000 consultants serve clients worldwide from 48 locations in 19 countries Our expertise delivers results Our optimism transforms outcomes Strategy Management Consulting Sia s Strategy Management Consulting global footprint and expertise in more than 40 sectors and services allow us to enhance our clients businesses worldwide We guide their projects and initiatives in strategy business transformation IT digital strategy Financial Institutions have drastically changed over the last decade driven by increased regulatory constraints diverse competition inside and beyond traditional banking organizations and emerging technologies reshaping long-standing ecosystems Sia s Financial Services Business Unit provides a comprehensive suite of core capabilities designed to address the diverse and evolving needs of our clients enabling them to navigate complex challenges seize new opportunities and achieve their strategic objectives in an increasingly competitive and dynamic business environment We are looking for a talented and motivated Data Engineer with strong experience in PySpark and Python to design build and maintain scalable data pipelines and infrastructure The successful candidate will support the delivery of data-driven insights by transforming raw data into clean curated datasets for analytics and machine learning applications Java experience is a plus and will be useful in hybrid environments Key Responsibilities Develop and optimize robust scalable data pipelines using PySpark and Python Clean transform and enrich large-scale datasets from structured and unstructured sources Implement data ingestion ETL ELT workflows and integration strategies across cloud and on-prem platforms Collaborate with data scientists analysts and business stakeholders to understand data requirements Ensure data quality integrity and lineage throughout the data lifecycle Participate in performance tuning troubleshooting and production support Contribute to best practices in data engineering including code versioning testing and CI CD Qualifications Required Qualifications Bachelor s degree in Computer Science Data Engineering or related field 3 years of experience in data engineering with a focus on PySpark and Python Strong hands-on experience with distributed data processing frameworks e g Apache Spark Solid understanding of SQL data modeling and relational databases Experience working with cloud platforms e g AWS Azure GCP Familiarity with workflow orchestration tools e g Airflow Azure Data Factory Preferred Qualifications Java experience for supporting hybrid data platforms and legacy integrations Exposure to data lakes delta lakes and modern data architectures Knowledge of containerization Docker Kubernetes and CI CD pipelines Familiarity with data governance security and compliance frameworks Additional Information We believe in supporting our team professionally and personally OUR COMMITMENT TO DIVERSITY At Sia we believe in fostering a diverse equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion Our commitment toward inclusion motivates dynamic collaboration with our clients building trust by creating an inclusive environment of curiosity and learning which affects lasting impact Please visit our for more information Sia is an equal opportunity employer All aspects of employment including hiring promotion remuneration or discipline are based solely on performance competence conduct or business needs