Senior Data Engineer

We are looking for a hands-on Senior Data Engineer to build and support scalable data pipelines and cloud-based data solutions. The ideal candidate will have strong experience in Python, PySpark, AWS, Airflow, and DevOps, with a focus on production-quality engineering and automation Responsibilities Design, build, and maintain scalable data pipelines deployed on AWS Develop robust data processing solutions using Python, Pandas, and PySpark Build and manage workflows through AWS Managed Workflows for Apache Airflow (MWAA) Develop and optimize data queries using AWS Athena to support efficient data analysis Automate infrastructure provisioning and deployment processes using Terraform and GitHub Actions Implement testing, monitoring, troubleshooting, and data-quality controls to ensure pipeline reliability Participate in code reviews and help drive strong engineering best practices across the team Collaborate with engineering, product, and business teams within an Agile environment Requirements A minimum of 3 years of relevant professional experience Strong core Python programming skills for building data engineering solutions Hands-on experience with Python Pandas for data manipulation and analysis Proficiency in PySpark for processing large-scale distributed data Experience with AWS MWAA or Apache Airflow for orchestrating and managing data workflows Working knowledge of AWS Athena for querying and analyzing data stored in AWS Experience using Terraform to automate infrastructure provisioning and management Familiarity with GitHub Actions for building automated CI/CD workflows Solid understanding of DevOps practices applied to data engineering environments Strong data engineering, debugging, and problem-solving skills Upper-intermediate English language skills or higher (B1) Nice to have Experience using GitHub Copilot to support development, code reviews, testing, and release management Familiarity with CI/CD practices and tooling for streamlined software delivery Experience working within Agile/Scrum environments Background in financial services or investment management industries Experience with Gen AI application development and applying Gen AI within the software development lifecycle (SDLC)