Aws Architect
Summary
Designs, builds, and manages enterprise-grade data lake and lakehouse solutions on AWS — from architecture and ingestion pipelines through transformation, governance, and production rollout. Core stack: Amazon S3, AWS Glue, Redshift, Athena, Lake Formation, EMR, Kinesis, Databricks, and Apache Spark.
Job Description: AWS Data Lake Architect
Experience: 5 to 7 Years
Location: Goregaon, Mumbai
Job Overview
An AWS Data Lake Architect is responsible for designing, building, and managing enterprise-grade data lake and lakehouse solutions on Amazon Web Services (AWS). The ideal candidate must have strong hands-on experience in AWS data architecture and a proven track record of delivering end-to-end implementation projects.
Key Responsibilities
- Architecture Design: Design and implement scalable data lakes and lakehouse solutions using Amazon S3 with Bronze, Silver, and Gold data layers.
- Data Ingestion: Develop secure and scalable data ingestion pipelines from databases, APIs, and file systems.
- Data Transformation & Processing: Implement data processing and orchestration solutions using AWS Glue, Databricks, Amazon EMR, AWS Lambda, and Apache Spark.
- Data Governance & Security: Implement data governance, security policies, and access controls using AWS Lake Formation.
- End-to-End Implementation: Lead and execute AWS Data Lake implementation projects, from architecture design and development to deployment and production rollout.
- Collaboration: Work closely with data engineering, security teams, and business stakeholders to deliver solutions aligned with business requirements.
Required Skills & Tools
- Strong hands-on experience with Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, AWS Lake Formation, Amazon EMR, and Amazon Kinesis.
- Experience with Databricks, Delta Lake, and/or Apache Spark.
- Strong understanding of data lake and lakehouse architecture, ETL/ELT pipelines, data modelling, and data processing.
- Mandatory Implementation Experience: Candidates must have successfully worked on approximately 5 to 6 end-to-end AWS Data Lake or related data engineering implementation projects.
- Candidates must have hands-on implementation experience, not solely production support or maintenance experience.
- Experience in solution design, development, testing, deployment, and go-live activities.
Qualifications & Education
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- AWS certifications such as AWS Certified Solutions Architect or relevant AWS data analytics certifications are preferred.