About the role
Your Role at Baxter:
We are seeking a highly motivated and experienced Senior Data Engineer to design, develop, and implement enterprise-scale data integration and data engineering solutions. The ideal candidate will have strong expertise in PySpark, Python, SQL, AWS, Snowflake, and API integrations, with experience delivering end-to-end data engineering projects from requirements gathering through production deployment. The role involves building scalable data pipelines, modernizing data platforms, integrating enterprise applications, and supporting business analytics through reliable and high-performing data solutions.
What you’ll be doing:
- Design, develop, and maintain end-to-end data integration and engineering solutions.
- Lead the complete project lifecycle including requirements analysis, solution design, development, testing, deployment, and production support.
- Build and optimize scalable ETL/ELT pipelines for data ingestion, transformation, and loading.
- Develop robust data processing frameworks using PySpark and Python.
- Design and optimize complex SQL queries and data transformations.
- Develop and support integrations using REST APIs and modern integration patterns.
- Implement and maintain cloud-based data solutions leveraging AWS services and Snowflake.
- Ensure data quality, performance, scalability, and reliability across data platforms.
- Collaborate with business stakeholders, architects, and application teams to deliver effective data solutions.
- Troubleshoot production issues and provide timely resolutions.
- Follow data governance, security, and compliance standards.
- Mentor junior team members and contribute to data engineering best practices.
What you’ll bring:
- 8–10 years of experience.
- Strong experience in PySpark, Python, and SQL for building scalable, high-performance data solutions.
- Expertise in developing and optimizing ETL/ELT pipelines, data transformations, and large-scale distributed data processing.
- Solid understanding of data warehousing, data modeling, and cloud-based data architectures.
- Hands-on experience with AWS services such as S3, Glue, Lambda, EMR, Step Functions, RDS, and CloudWatch.
- Experience working with Snowflake to build and manage modern data platforms and data lakes.
- Knowledge of performance tuning, automation, and best practices for cloud-native data solutions.
- Experience with Git, CI/CD, and DevOps practices.
- Familiarity with Agile/Scrum methodologies.
- Strong problem-solving skills and a passion for building reliable, scalable data products.
Nice to have:
- Experience with Informatica PowerCenter/IICS for enterprise data integration and migration projects.
- Experience with IBM DataStage, including ETL development, performance tuning, and modernization initiatives.