Data & AWS Architect

Posted 22 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
4M-6M Annually
Expert/Leader
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Design, implement, and optimize scalable, secure AWS data architectures and high-performance ETL/ELT pipelines. Build batch and real-time data processing solutions using Spark (Scala), Glue, EMR, and orchestration tools; manage Redshift, DynamoDB, Kinesis, Athena, OpenSearch, and monitoring/security services. Lead cloud migration, IaC with CloudFormation, cost and performance tuning, governance, and cross-functional stakeholder collaboration.
Summary Generated by Built In

This role is for one of the Weekday's clients

Salary range: Rs 4000000 - Rs 5500000 (ie INR 40-55 LPA)

Experience: 10+ yrs

Location: Bengaluru

Job Type: full-time

We are seeking an experienced AWS Data Architect with deep expertise in cloud data engineering, scalable data architecture, and AWS-native technologies. This role is ideal for professionals with extensive experience designing enterprise-grade data platforms and building high-performance data pipelines that support analytics, reporting, and business-critical applications.

As an AWS Data Architect, you will be responsible for designing, implementing, and optimizing cloud-based data solutions using a wide range of AWS services. You will collaborate with business stakeholders, architects, developers, and data engineering teams to translate complex business requirements into secure, scalable, and reliable data architectures. This role requires strong expertise in data modelling, ETL development, real-time and batch processing, cloud security, and infrastructure automation while ensuring performance, governance, and cost optimization across AWS environments.


RequirementsKey Responsibilities
  • Design and implement scalable, secure, and high-performance data architectures on AWS to support enterprise data initiatives.
  • Develop and maintain robust data pipelines using Spark (Scala), AWS Glue, Oozie, and other cloud-native technologies for batch and real-time processing.
  • Build and optimize ETL/ELT workflows that efficiently ingest, transform, and process large volumes of structured and unstructured data.
  • Configure, manage, and optimize AWS services including EMR, Redshift, DynamoDB, Kinesis, Athena, OpenSearch, CloudWatch, Macie, CloudFormation, API Gateway, SNS, SQS, and DMS.
  • Design cloud data models that support analytics, reporting, operational workloads, and business intelligence requirements.
  • Collaborate with cross-functional teams to gather business requirements and deliver scalable technical solutions aligned with organizational objectives.
  • Monitor system performance, identify bottlenecks, and implement optimization strategies to improve scalability, reliability, and cost efficiency.
  • Implement best practices for cloud security, data governance, compliance, and privacy using AWS-native security and monitoring services.
  • Develop Infrastructure as Code (IaC) solutions using AWS CloudFormation to automate cloud resource provisioning and deployment.
  • Troubleshoot complex issues related to data ingestion, processing, storage, and integration across AWS environments.
  • Support cloud migration initiatives and integrate enterprise data sources with modern AWS data platforms.
  • Maintain technical documentation, architecture diagrams, and operational procedures while ensuring adherence to cloud engineering best practices.
What Makes You a Great Fit
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.
  • 10+ years of experience in data architecture, cloud data engineering, and enterprise-scale AWS solutions.
  • Strong expertise in AWS Architecture and designing scalable cloud-native data platforms.
  • Hands-on experience with AWS services including EMR, Redshift, DynamoDB, Kinesis, Athena, OpenSearch, CloudWatch, Macie, CloudFormation, API Gateway, SNS, SQS, DMS, and AWS Glue.
  • Advanced proficiency in Spark with Scala for large-scale distributed data processing.
  • Strong knowledge of data modelling, ETL/ELT design, workflow orchestration, and cloud data architecture principles.
  • Experience building real-time and batch data processing solutions with a focus on performance and reliability.
  • Expertise in implementing cloud security, monitoring, governance, and compliance best practices.
  • Familiarity with containerization technologies such as Docker and Kubernetes, along with machine learning pipelines and advanced AWS analytics services, is an added advantage.
  • AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect certification is preferred.
  • Excellent analytical, problem-solving, stakeholder management, and communication skills with the ability to collaborate effectively across cross-functional teams.

Skills Required

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or related discipline.
  • 10+ years experience in data architecture, cloud data engineering, and enterprise-scale AWS solutions.
  • Advanced proficiency in Spark with Scala for large-scale distributed data processing.
  • Hands-on experience with AWS services: EMR, Redshift, DynamoDB, Kinesis, Athena, OpenSearch, CloudWatch, Macie, CloudFormation, API Gateway, SNS, SQS, DMS, AWS Glue.
  • Design and implement scalable, secure, high-performance cloud-native data platforms and data models.
  • Experience building real-time and batch data processing solutions and robust ETL/ELT workflows.
  • Experience with workflow orchestration tools (e.g., Oozie) and troubleshooting complex data ingestion/processing issues.
  • Expertise in cloud security, monitoring, governance, compliance, and cost optimization on AWS.
  • Experience developing Infrastructure as Code (IaC) solutions using AWS CloudFormation.
  • Familiarity with containerization (Docker, Kubernetes) and machine learning pipelines.
  • AWS Certified Data Analytics - Specialty or AWS Certified Solutions Architect (preferred).
  • Strong analytical, problem-solving, stakeholder management, and communication skills.
Am I A Good Fit?
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The Company
Year Founded: 2021

What We Do

Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.

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