Job Description
About Ascendion
Ascendion is a leader in AI-powered software engineering, helping businesses innovate faster, smarter, and with greater impact. We partner with Global 2000 clients across North America, UK, Europe, and APAC to solve complex challenges in data, experience design, software product engineering, and workforce transformation. Powered by expert engineers, thousands of AI agents, and our Engineering to the Power of AI™ (EngineeringAI) method, we deliver measurable outcomes that build trust, unlock value, and accelerate growth. Learn more at ascendion.com
Ascendion | Engineering to elevate life
We have a culture built on opportunity, inclusion, and a spirit of partnership. Come, change the world with us:
Build the coolest tech for world's leading brands
Solve complex problems – and learn new skills
Experience the power of transforming digital engineering for Fortune 500 clients
Master your craft with leading training programs and hands-on experience
Experience a community of change makers!
Join a culture of high-performing innovators with endless ideas and a passion for tech. Our culture is the fabric of our company, and it is what makes us unique and diverse. The way we share ideas, learning, experiences, successes, and joy allows everyone to be their best at Ascendion.
Key Responsibilities
Design, develop, and maintain scalable ETL pipelines using Python and PySpark
Build and optimize data workflows on AWS services such as S3, Glue, Lambda, Redshift, and EMR
Perform data ingestion, transformation, and validation from multiple data sources
Optimize data processing performance and ensure data quality and integrity
Implement data lake and data warehouse solutions
Collaborate with cross-functional teams to understand data requirements
Automate data workflows and scheduling using tools like Airflow or AWS Step Functions
Monitor and troubleshoot data pipeline issues
Ensure security, governance, and compliance of data systems
Required Skills & Qualifications
Strong experience in Python programming
Hands-on experience with PySpark and Spark-based data processing
Solid understanding of ETL/ELT concepts and data pipeline design
Experience with AWS services (S3, Glue, Redshift, Lambda, EMR, Athena)
Proficiency in SQL and working with relational and non-relational databases
Experience with workflow orchestration tools (Airflow, Luigi, etc.)
Knowledge of data modeling and data warehousing concepts
Familiarity with version control systems like Git
