Hiring Data Engineer || 5+ yrs || Remote

Job Title: Data Engineer

Experience: 5+ Years

Location: Remote

Notice Period : - Immediate joiner (under 15-20 days)

Mandate Skills: AWS data engineering experience, including S3, Glue, Athena, Lambda, Step Functions, Lake Formation, KMS, and CloudWatch, Advanced SQL, Python, Data lake, Apache Iceberg

Good to have skills : CI/CD and DevOps (Familiar), Git, JIRA, SonarQube

NOTE: Please attach your resume @ and add your expected CTC details

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What Your Day Would Be Like

• Design, implement, and maintain ETL pipelines on AWS using Step Functions, Glue, Lambda, and S3, aligned with Iceberg-based Lakehouse patterns.
• Build and optimize SQL transformations for Athena and Iceberg tables, including implementation of star and snowflake schemas from YAML table definitions and SQL transformations.
• Develop and maintain data models (fact and dimension tables) that power analytics and reporting in the data lake.
• Operate data ingestion pipelines and manage Lake Formation permissions to ensure secure and governed data access.
• Implement data quality checks and alerting using the in-repository data quality framework and AWS services.
• Provision, maintain, and evolve infrastructure using Terraform /AWS CDK as the Infrastructureas-Code framework.
• Contribute to CI/CD pipelines, including testing, linting, and deployments.
• Ensure data security and compliance through KMS encryption, IAM, Lake Formation controls, and audit logging.
• Monitor pipelines and infrastructure using CloudWatch and event-driven alerts.
• Collaborate effectively with cross-functional stakeholders using Atlassian project management tools, demonstrating strong stakeholder management and clear communication throughout the delivery lifecycle.
• Leverage AI-assisted development tools to accelerate troubleshooting, code reviews, and pipeline optimization while maintaining high quality and security standards.

We Would Love to Hear From You If You Have

• A bachelor’s or master’s degree in a technical field.
• 5+ years of experience in data engineering or a similar role.
• Strong AWS data engineering experience, including S3, Glue, Athena, Lambda, Step Functions, Lake Formation, KMS, and CloudWatch.
• Advanced SQL skills for complex transformations and data modeling.
• Proficiency in Python.
• Experience with data lake architectures and Apache Iceberg (or similar table formats).
• Familiarity with CI/CD and DevOps practices.
• Comfort using AI tools responsibly within software development workflows.

Preferred Qualifications

• AWS, Snowflake certifications.
• Experience using Terraform/AWS CDK as Infrastructure as Code at scale.

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NOTE: Please attach your resume @ and add your expected CTC details

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About IGT Solutions

IGT Solutions is a next-gen Tech Services and Customer Experience (CX) company. It enables personalized, meaningful, and effective interactions by combining cutting-edge technology and innovative solutions with the power of Gen AI to deliver exceptional end-user experiences. With the ability to integrate human and digital intelligence seamlessly, it is a trusted partner for managing end-to-end transformation journeys for global majors across industries. Established in 1998, IGT Solutions has more than 90 global marquee customers and 25,000+ experts servicing client processes from 31 global delivery centers across 13 countries. IGT Solutions' service offerings include data & analytics, digital transformation, systems integration, platform solutions, AI/ML, and Gen AI-led industry and enterprise solutions, intelligent automation and analytics, and a full spectrum of BPM services and solutions.

It is our policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds.