Data Engineer - AWS

AWS Data Engineer (PySpark)Location: Northampton - 3 Days Onsite (Hybrid Mode)Experience: 5+ YearsEmployment Type: ContractJob SummaryWe are looking for an experienced AWS Data Engineer with strong PySpark expertise to design, develop, and optimize scalable data pipelines and cloud-based data platforms. The ideal candidate will have hands-on experience in building ETL/ELT solutions on AWS, processing large datasets using Spark, and implementing data engineering best practices.Key ResponsibilitiesDevelop and maintain scalable data pipelines using PySpark and AWS services.Build robust ETL/ELT workflows for ingesting, transforming, and loading data from multiple sources.Design and manage data lakes and data warehouse solutions on AWS.Work with AWS services such as S3, Glue, EMR, Redshift, Lambda, Athena, IAM, and CloudWatch.Optimize Spark jobs for performance, scalability, and cost efficiency.Implement data quality, validation, and monitoring processes.Collaborate with business stakeholders, analysts, and architects to deliver data solutions.Support production deployments, troubleshooting, and performance tuning.Maintain technical documentation and follow data governance standards.Required Skills5+ years of Data Engineering experience.Strong hands-on experience with PySpark and Apache Spark.Extensive experience with AWS Cloud Services:S3GlueEMRRedshiftAthenaLambdaIAMCloudWatchStrong programming skills in Python.Advanced SQL development and query optimization skills.Experience building large-scale ETL/ELT pipelines.Knowledge of Data Warehousing and dimensional data modeling.Experience with Git and CI/CD practices.Preferred SkillsExperience with Databricks.Knowledge of Apache Airflow or AWS Step Functions.Experience with Kafka or real-time data processing.Exposure to Terraform and Infrastructure as Code (IaC).Experience with Snowflake or Lakehouse architectures.AWS Certification is highly desirable.