AWS Data Architect

Brillio

10 - 16 years

25 - 40 Lacs

pune chennai bengaluru

Posted:-1 days ago| Platform:

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Skills Required

data lake data architecture aws glue athena aws aws lambda

Work Mode

Hybrid

Job Type

Full Time

Job Description

Role Overview

We are seeking an experienced AWS Data Architect with strong hands-on expertise in designing, building, and optimizing scalable data lake and analytics platforms on AWS. The ideal candidate will combine deep technical proficiency in AWS services with a strong understanding of data architecture principles, governance, and best practices for analytical enablement.

Key Responsibilities

Architect and Design: Define and implement scalable, secure, and cost-efficient AWS-based data lake architectures using S3, Glue, Athena, and Lake Formation.
Data Engineering: Develop robust ETL/ELT pipelines using PySpark, Glue, and Lambda for batch and near-real-time data ingestion and transformation.
Data Modeling: Design logical and physical data models, implement schema evolution, partitioning strategies, and efficient metadata management.
Lifecycle Management: Manage the complete data lifecycle from raw ingestion to curated and analytical layers ensuring data quality, lineage, and traceability.
Integration: Enable seamless data consumption by downstream systems such as Redshift Spectrum, QuickSight, SageMaker, and other BI or ML platforms.
Governance & Security: Enforce robust data governance, access control, and compliance through IAM, KMS, CloudTrail, and Lake Formation.
Data Quality: Implement and automate data validation frameworks using tools such as Deequ or Great Expectations.
Automation & DevOps: Build infrastructure as code (IaC) using AWS CDK or Terraform, and orchestrate CI/CD pipelines with GitHub Actions or AWS CodePipeline.
Monitoring & Optimization: Set up observability, performance tuning, and cost optimization through CloudWatch, Glue job optimization, and Athena query tuning.
Leadership & Guidance: Collaborate with cross-functional teams, mentor data engineers, and define best practices for scalable data engineering and architecture.

Required Skills & Qualifications

Proven experience architecting and implementing AWS data lake and analytics ecosystems.
Hands-on expertise in AWS Glue, S3, Athena, Lambda, Redshift, and Lake Formation.
Strong programming and ETL skills using PySpark / Python.
Deep understanding of data modeling, data ingestion patterns, and schema evolution.
Knowledge of data governance, security, and compliance frameworks in cloud environments.
Familiarity with CI/CD, IaC, and DevOps tools (CDK, Terraform, GitHub Actions, CodePipeline).
Experience with data quality frameworks (Deequ, Great Expectations).
Strong problem-solving, analytical, and communication skills.
Bachelor's or Master’s degree in Computer Science, Data Engineering, or related field.

Preferred Qualifications

AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Professional.
Experience with real-time data streaming (Kinesis, Kafka, or MSK).
Exposure to machine learning pipelines and MLOps using SageMaker.

Experience working in Agile environments.

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