Data Engineer

Location: Buffalo, NY Salary: $70.00 USD Hourly - $75.00 USD Hourly Description:
Title :
Data Engineer

Duration: 12 months+ Open Contract

Location:

Buffalo, NY remote
Interview information:
Single 90-minute technical interview

Must Haves:

• Project Management

• Strong database experience:

• DDL / DML

• Data querying, insertion, and manipulation

• Strong programming foundation (language-agnostic mindset):

• Java, Python, Ruby, or JavaScript/Type Script

• Experience with:

• CI/CD pipelines (Git Lab preferred)

• Git/version control

• Experience with APIs (consumption and integration)

• Solid understanding of:

• Test data management

• Data obfuscation / masking

• Synthetic data generation

• Experience with cloud platforms (Azure strongly preferred)

• Ability to work with and across:

• Legacy systems

• Modern cloud environments

• Strong communication skills (working with app teams, stakeholders)

• Ability to operate as a self-starter in a fast-paced environment

Nice to Haves:

• Experience with Delphix (DCT / Compliance Tool) or similar:

• Broadcom or other data masking solutions

• Containerization experience:

• Docker

• Kubernetes (basic understanding is sufficient)

• Exposure to quality assurance/testing practices

• Financial services experience (highly preferred)

• Data conditioning within banking environments

• Experience with mainframe systems:

• VSAM files or legacy data platforms

• Familiarity with AI-assisted tools (Copilot, Git Lab Duo)

Key Responsibilities:

• Support enterprise test data management initiatives

• Perform data obfuscation/masking for non-production environments

• Enable synthetic data generation to reduce use of sensitive data

• Work across:

• Databases

• APIs

• Mainframe and cloud systems

• Support teams requesting test data across the bank

• Integrate data processes into CI/CD pipelines

Ideal Candidate Traits:

• Able to communicate effectively across all levels (technical & leadership)

• Adaptable in a mixed/legacy + modern tech environment

• Confident in technical knowledge (can explain decisions clearly)

• Strong ability to understand the "big picture"

• Comfortable working in complex enterprise ecosystems

Title :
Data Engineer

Duration: 12 months+ Open Contract

Location:

Buffalo, NY remote
Interview information:
Single 90-minute technical interview

Must Haves:

• Project Management

• Strong database experience:

• DDL / DML

• Data querying, insertion, and manipulation

• Strong programming foundation (language-agnostic mindset):

• Java, Python, Ruby, or JavaScript/Type Script

• Experience with:

• CI/CD pipelines (Git Lab preferred)

• Git/version control

• Experience with APIs (consumption and integration)

• Solid understanding of:

• Test data management

• Data obfuscation / masking

• Synthetic data generation

• Experience with cloud platforms (Azure strongly preferred)

• Ability to work with and across:

• Legacy systems

• Modern cloud environments

• Strong communication skills (working with app teams, stakeholders)

• Ability to operate as a self-starter in a fast-paced environment

Nice to Haves:

• Experience with Delphix (DCT / Compliance Tool) or similar:

• Broadcom or other data masking solutions

• Containerization experience:

• Docker

• Kubernetes (basic understanding is sufficient)

• Exposure to quality assurance/testing practices

• Financial services experience (highly preferred)

• Data conditioning within banking environments

• Experience with mainframe systems:

• VSAM files or legacy data platforms

• Familiarity with AI-assisted tools (Copilot, Git Lab Duo)

Key Responsibilities:

• Support enterprise test data management initiatives

• Perform data obfuscation/masking for non-production environments

• Enable synthetic data generation to reduce use of sensitive data

• Work across:

• Databases

• APIs

• Mainframe and cloud systems

• Support teams requesting test data across the bank

• Integrate data processes into CI/CD pipelines

Ideal Candidate Traits:

• Able to communicate effectively across all levels (technical & leadership)

• Adaptable in a mixed/legacy + modern tech environment

• Confident in technical knowledge (can explain decisions clearly)

• Strong ability to understand the "big picture"

• Comfortable working in complex enterprise ecosystems

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