Senior Data Engineer – AWS Glue & Snowflake

Senior Data Engineer – AWS Glue & SnowflakeWe are seeking a highly skilled Senior Data Engineer with deep expertise in AWS Glue and cloud-based data engineering to design, build, and optimize scalable data integration solutions. This role will be responsible for developing enterprise-grade ETL/ELT pipelines, managing large-scale data movement, and supporting modern analytics platforms built on AWS and Snowflake. The ideal candidate combines strong software engineering practices with hands-on experience in AWS data services, PySpark development, and cloud-native architecture.Key ResponsibilitiesDesign, develop, and maintain scalable ETL/ELT pipelines using AWS Glue.Build and optimize Glue Jobs, Crawlers, Data Catalogs, and Glue Workflows.Develop PySpark and Python-based transformation logic for large-scale data processing.Create reusable data ingestion frameworks and automation capabilities.Implement robust error handling, monitoring, and recovery mechanisms.AWS Data Platform EngineeringDesign and maintain data solutions leveraging AWS services including:AWS GlueAmazon S3IAMLake FormationCloudWatchLambdaStep FunctionsEventBridgeEnsure secure, scalable, and cost-effective data platform operations.Optimize AWS resource utilization and processing performance.Snowflake IntegrationBuild and maintain data pipelines that ingest, transform, and load data into Snowflake.Optimize Snowflake loading patterns, staging strategies, and transformation workflows.Collaborate with data modelers and analytics teams to support reporting and business intelligence initiatives.Data Quality & GovernanceImplement data quality controls, validation routines, and monitoring processes.Support data lineage, metadata management, and governance requirements.Troubleshoot data anomalies and performance bottlenecks across the platform.Engineering & DevOpsDevelop solutions using Infrastructure as Code and CI/CD best practices.Utilize Git-based source control and automated deployment pipelines.Participate in architecture reviews and technical design discussions.Mentor junior engineers and promote engineering standards.Required QualificationsBachelor's degree in Computer Science, Information Systems, Engineering, or related field.5+ years of experience in Data Engineering or ETL development.3+ years of hands-on AWS Glue development experience.Strong Python and PySpark programming skills.Advanced SQL development skills.Experience building cloud-native data pipelines on AWS.Experience integrating with Snowflake or similar cloud data warehouses.Knowledge of data warehousing concepts and dimensional modeling.Experience working with large datasets and distributed processing frameworks.Preferred QualificationsAWS Certified Data Engineer – Associate or Specialty certification.Experience with Apache Spark optimization and tuning.Experience with dbt.Experience with Airflow, Step Functions, or other orchestration tools.Experience with Kafka, Kinesis, or streaming data platforms.Experience with healthcare, insurance, financial services, or other regulated industries.Familiarity with Kimball dimensional modeling methodologies.Technical Skills RequiredAWS GluePySparkPythonSQLAmazon S3SnowflakeData WarehousingETL/ELT DevelopmentGitTechnical Skills PreferreddbtAirflowStep FunctionsLambdaLake FormationTerraformCloudFormationKafka/KinesisDockerSuccess FactorsStrong software engineering mindset.Expertise in building reliable and scalable data pipelines.Ability to troubleshoot complex data integration issues.Strong communication and collaboration skills.Focus on automation, performance optimization, and operational excellence.Ideal Candidate ProfileAn engineer who can independently design a data ingestion framework, write PySpark transformations in AWS Glue, optimize Snowflake loads, automate deployments through CI/CD, and serve as the technical expert for enterprise data integration initiatives.