Senior Data Engineer (AWS)

EXL Service
Role: Senior Data Engineer
Experience: 5+ Years
Location: All EXL Location
Work Mode: Hybrid
Summary:
We are seeking an experienced Senior Data Engineer with a strong background in designing, building, and optimizing scalable data pipelines in AWS. You will play a critical role in shaping our data architecture, enabling data-driven decision-making, and supporting advanced analytics across the organization.
Roles and Responsibilities:
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Design, build, and maintain robust, scalable data pipelines using AWS services.
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Develop and optimize ETL/ELT processes to ingest, transform, and load large datasets from multiple sources.
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Work with structured and unstructured data, ensuring high data quality and integrity.
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Implement and manage data lakes and data warehouses using AWS technologies.
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Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver solutions.
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Monitor, troubleshoot, and optimize data workflows and queries for performance and cost efficiency.
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Implement infrastructure as code (IaC) practices using Terraform.
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Integrate CI/CD pipelines and DevOps practices using Azure DevOps.
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Ensure data security, governance, and compliance best practices are followed.
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Document data architecture, processes, and standards.
Must Have Skills:
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10+ years of experience in Data Engineering or related roles with a least 5+ of these building solutions in AWS.
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Hands-on expertise with key AWS services:
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S3, Lambda, Glue, Redshift, Athena, Step Functions, EventBridge, SQS, SNS, IAM, Cloudwatch, VPC
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Solid understanding of data warehousing and data lake architectures
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Expertise in the design and development of data marts, including dimensional modeling (star/snowflake schemas) and building optimized, business-focused data models for analytics and reporting
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Strong expertise with SQL, Python and Spark.
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Experience with creating of AWS resources using Infrastructure as Code (IaC), preferably through Terraform.
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Familiarity with DevOps practices and tools, such as Azure DevOps.
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Experience with version control systems (e.g., Git).
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Strong problem-solving skills and attention to detail.
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One or more AWS certifications (e.g., AWS Solutions Architect, Certified Data Engineer, DevOps etc).
Education: Bachelor’s degree in computer science, Software Engineering, MIS or equivalent combination of education and experience
Key Skills: SQL, Python, Spark, AWS [S3, Lambda, Glue, Redshift, Athena, Step Functions, Event Bridge, SQS, SNS, IAM, CloudWatch, VPC]