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pditechnologies

Data Engineer II

  • Chennai
  • Full-time
  • Posted

Skills

  • AWS
  • Apache Spark
  • CI/CD
  • Communication
  • Git
  • NetSuite
  • Problem Solving
  • Python
  • SQL
  • Salesforce
  • Teamwork
  • Terraform

Job description

Key Responsibilities

•

Design, develop, and maintain cloud-based data pipelines supporting enterprise reporting and analytics.

•

Build and optimize ETL/ELT processes using AWS-native data services and modern data engineering practices.

•

Integrate enterprise source systems, including Salesforce, NetSuite, and other business applications, into centralized data platforms.

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Develop and maintain scalable data models supporting reporting and business intelligence initiatives.

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Monitor pipeline performance, troubleshoot data issues, and implement improvements to ensure data accuracy and reliability.

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Partner with business stakeholders to understand reporting requirements and translate them into technical solutions.

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Support data governance initiatives by maintaining data quality, metadata, and documentation.

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Contribute to automation, continuous integration, and infrastructure-as-code practices to improve development efficiency.

•

Participate in code reviews and promote engineering best practices across the team.

Qualifications

•

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field, or equivalent experience.

•

2-4 years of experience in data engineering or cloud data platform development.

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Experience developing data pipelines using AWS services such as S3, Glue, Redshift, AppFlow, and Step Functions.

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Experience working with SQL, Python, and PySpark.

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Understanding of dimensional modeling, data warehousing concepts, and modern data lake technologies.

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Experience integrating enterprise applications such as Salesforce, NetSuite, or similar SaaS platforms.

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Familiarity with Git, CI/CD pipelines, and Infrastructure as Code (Terraform preferred).

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Practical experience with applying AI/ML techniques to data engineering problems, such as automated data quality checks, anomaly detection, or intelligent pipeline monitoring

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Strong analytical and problem-solving skills.

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Excellent collaboration and communication skills.

Behavioral Competencies

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Ensures Accountability

•

Manages Complexity

•

Communicates Effectively

•

Balances Stakeholders

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Collaborates Effectively

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