Advent Global Solutions Inc.
Lead AWS DATA Engineer ( 15 years): Immediate interviews
Malvern, Pennsylvania · Junior
Sponsorship not specifiedDetected 50 days ago
PythonJavaDistributed SystemsGitSQLDynamoDBRedshiftAWSTerraformCI/CDDatadogKafkaMachine LearningSparkAirflowData EngineeringAI OrchestrationCybersecurityProject ManagementEHR/EMRCommunication
About the role
- • *We have placed multiple resources with this client manager and can setup immediate interviews.**
- Job Description: Tech Lead- Data Engineer
Responsibilities
- Architect, build, and maintain event-driven data pipelines using AWS services such as Kinesis, MSK/Kafka, Lambda, Step Functions, SQS/SNS, and Glue/EMR.
- Develop ETL/ELT workflows using Python and PySpark, ensuring performance, scalability, and cost efficiency.
- Implement and optimize Spark-based data transformations, partitioning strategies, and data processing frameworks.
- Design and manage data lake and warehouse structures using S3, Glue Catalog, Athena, and/or Redshift.
- Build streaming solutions with checkpointing, stateful transformations, idempotency, and schema evolution.
- Implement data security best practices including IAM, encryption (KMS), networking, and governance.
- Create reusable frameworks, internal libraries, and CI/CD pipelines for automated deployments.
- Collaborate with data scientists, analysts, and business teams to deliver well-modeled, reliable datasets.
- Lead design reviews, mentor junior engineers, and contribute to engineering best practices.
Skills
- Java| AWS | Python | PySpark | Event-Driven Pipelines | Data Architecture
- Ensure high standards of data quality, observability, monitoring, and alerting (CloudWatch, Datadog, etc.).
- professional experience in Data Engineering.
- Strong expertise in Python and PySpark for large-scale data processing.
- Advanced hands-on experience with AWS (S3, Glue, EMR, Lambda, Step Functions, Kinesis/MSK, DynamoDB, Athena, Redshift).
- Deep experience building event-driven and streaming data pipelines.
- Strong SQL experience for analytical and ETL workloads.
- Hands-on experience with workflow orchestration tools such as Airflow or Step Functions.
- Experience with CI/CD, Git, and Infrastructure-as-Code (Terraform or CloudFormation).
- Strong understanding of distributed systems, Spark performance tuning, data modeling, and cloud cost optimization.
- Knowledge of data security, encryption, networking, and compliance best practices in cloud environments.
- Core Java~Project Management
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