cloudingest inc

cloudingest inc

AWS Data Engineer (W2 Only) (Any visa expect H1B)

Philadelphia, Pennsylvania · Senior

Sponsorship not specifiedDetected 116 days ago
PythonSQLAWSSparkData EngineeringCommunicationProblem Solving

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odds of building a lasting career here

37Risky
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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Context, not a finding about this posting: of this employer's 3 green-card filings in this occupation, 67% were for a worker who already held the job.

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About the role

  • Please share Relevant profiles to Srikanth@cloudingest.com
  • We are seeking an experienced AWS Data Engineer to support a leading financial services organization. The ideal candidate will have strong expertise in designing, developing, and optimizing cloud-based data pipelines and ETL/ELT solutions using AWS services. This role requires hands-on experience with AWS data engineering tools, Python programming, and

Responsibilities

  • Design, develop, and maintain scalable data pipelines on AWS.
  • Build and optimize ETL/ELT workflows using AWS Glue, Python, PySpark, and Spark.
  • Develop serverless data processing solutions using AWS Lambda, EventBridge, and Step Functions.
  • Perform data migration and integration activities using AWS DMS and AWS DataSync.
  • Manage and optimize data storage solutions using Amazon S3.
  • Implement secure access controls and governance using AWS IAM.
  • Collaborate with business stakeholders, architects, and development teams to deliver data-driven solutions.

Nice to have

  • 7+ years of Data Engineering experience.
  • Strong hands-on experience with AWS-based data platforms.
  • Expertise in Python and SQL development.
  • Financial Services or Banking domain experience is highly preferred.
  • Strong problem-solving and communication skills.

Visa & Work Authorization

  • Visa: Any (Except H1B) (W2 Only)
  • OPT and Any EAD's are Most Welcome

This listing is sourced directly from cloudingest inc's careers page and normalized into a canonical job model.