Lead Data Engineer (15+ Years)

Job Type: Full Time
Job Location: Malvern PA
Duration: 6 Months

Mandatory Skills: Data Architecture | Java| AWS | Python | PySpark | Event-Driven Pipelines

Summary:

We are seeking an experienced Tech lead- Data Engineer (15+ years) with a strong background in Java, AWS, Python, PySpark, and event-driven architectures. You will design and build scalable batch and streaming data pipelines, optimize cloud data platforms, and deliver high-quality, reliable datasets that support analytics, reporting, and machine learning workloads.

Key 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.
 Ensure high standards of data quality, observability, monitoring, and alerting (CloudWatch, Datadog, etc.).
 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.

Required Qualifications

 15+ years of 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 Soft Skills
 Strong design and architectural understanding Excellent communication and stakeholder interaction skills Ability to work in a globally distributed team

Skills: Core Java, Project Management
Experience Required: 8-10

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