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Associate Architect - Data (AWS + AtScale)
IN KA Bengaluru
Open 6 months, first seen by us 180 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Before you apply
- New graduates
- Entry level
Job title: Associate Architect - Data (AWS + AtScale)
What you’ll work on
Full postingDesign and implement data warehouses and data lakes/lakehouses on AWS
Build semantic layers with logical models, virtual cubes and central metric definitions
Build ETL and metadata frameworks using AWS Glue
Orchestrate modular, resilient data pipelines using native AWS services
Enforce row/column-level security across BI tools such as QuickSight, Tableau and Power BI
From the employer’s posting
designing and implementing data warehouses and data lakes/lakehouse on AWS
Strong understanding of semantic modeling, including logical data models, virtual cubes, and centralized metric definitions (single source of truth).
Developing ETL and metadata frameworks using AWS Glue.
Proven experience in architecting and implementing data pipelines using native AWS services in a modular and resilient manner.
enforce row/column-level security aligned with governance frameworks
Posting record
Report an errorOpen 6 monthsWe first saw this posting 180 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- May 8, 2026180 days ago
- Recorded sightings
- 228
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Apr 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Quantiphi is hiring
30 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is steady
- Takes jobs down at a usual pace
- 3% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- DynamoDB
- MongoDB
- MySQL
- NoSQL
- PostgreSQL
- Power BI
- Redshift
- S3
- Tableau
- Terraform
- PySpark
Where the posting names them
- Ability to integrate semantic layers with BI tools (QuickSight, Tableau, Power BI) and enforce row/column-level security aligned with governance frameworks. - Strong programming capability in Python and PySpark for large-scale data processing. - Proficiency in writing complex SQL queries, analytical functions, and performance tuning for large datasets.
- Strong programming capability in Python and PySpark for large-scale data processing. - Proficiency in writing complex SQL queries, analytical functions, and performance tuning for large datasets. - Familiarity with NoSQL databases such as Amazon DynamoDB, MongoDB, or DocumentDB.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi! Role : Associate Architect - Data (AWS + AtScale) Experience : 5 - 13 Years
Must have Skills: - 5+ years of experience in designing and implementing data warehouses and data lakes/lakehouse on AWS. - Hands-on experience with AtScale or similar semantic layer tools to enable governed, business-friendly data access across BI platforms.
- Proven success working with globally distributed teams in collaborative delivery environments. - Deep working knowledge across key AWS Data & Analytics services, including: - Building large-scale data lake architectures on Amazon S3 and open table formats
- Building large-scale data lake architectures on Amazon S3 and open table formats - Implementing governance and cataloging through AWS Lake Formation. - Developing ETL and metadata frameworks using AWS Glue.
- Implementing governance and cataloging through AWS Lake Formation. - Developing ETL and metadata frameworks using AWS Glue. - Leveraging AWS Lambda for serverless data processing.
- Developing ETL and metadata frameworks using AWS Glue. - Leveraging AWS Lambda for serverless data processing. - Running distributed data workloads on Amazon EMR.
- Running distributed data workloads on Amazon EMR. - Enabling real-time data pipelines with AWS Kinesis (Data Streams and Firehose). - Orchestrating pipelines using AWS Step Functions/Amazon MWAA/similar services.
- Enabling real-time data pipelines with AWS Kinesis (Data Streams and Firehose). - Orchestrating pipelines using AWS Step Functions/Amazon MWAA/similar services. - Designing and optimizing schemas and query performance on Amazon Redshift, including Spectrum and Serverless features.
- Managing operational databases using Amazon RDS across engines such as PostgreSQL, MySQL, and Aurora. - Integrating and migrating data using AWS DMS, Glue Connectors, EventBridge, SNS, and SQS. - Strong understanding of semantic modeling, including logical data models, virtual cubes, and centralized metric definitions (single source of truth).
- Strong understanding of partitioning, indexing, scaling approaches, and query optimization techniques. - Proven experience in architecting and implementing data pipelines using native AWS services in a modular and resilient manner. - Solid understanding of data modeling concepts, including dimensional, normalized, and lakehouse patterns.
- Familiarity with data virtualization (e.g., Amazon QuickSight,PowerBI, Tableau) and data governance tools (e.g., Collibra). - Managing security, monitoring, and compliance with AWS IAM, Secrets Manager, CloudWatch, CloudTrail, and KMS. - Experience with AI-assisted development tools such as GitHub Copilot, Amazon Kiro (or similar GenAI IDEs) for improving developer productivity, code generation, and pipeline acceleration
- Proficiency in writing complex SQL queries, analytical functions, and performance tuning for large datasets. - Familiarity with NoSQL databases such as Amazon DynamoDB, MongoDB, or DocumentDB. - Strong understanding of partitioning, indexing, scaling approaches, and query optimization techniques.
- Querying large datasets interactively using Amazon Athena. - Managing operational databases using Amazon RDS across engines such as PostgreSQL, MySQL, and Aurora. - Integrating and migrating data using AWS DMS, Glue Connectors, EventBridge, SNS, and SQS.
- Experience optimizing performance using query pushdown, caching, and aggregate awareness over platforms like Redshift and Athena. - Ability to integrate semantic layers with BI tools (QuickSight, Tableau, Power BI) and enforce row/column-level security aligned with governance frameworks. - Strong programming capability in Python and PySpark for large-scale data processing.
- Exposure to IaC tools like Terraform and to CI/CD tools - Familiarity with data virtualization (e.g., Amazon QuickSight,PowerBI, Tableau) and data governance tools (e.g., Collibra). - Managing security, monitoring, and compliance with AWS IAM, Secrets Manager, CloudWatch, CloudTrail, and KMS.
- Orchestrating pipelines using AWS Step Functions/Amazon MWAA/similar services. - Designing and optimizing schemas and query performance on Amazon Redshift, including Spectrum and Serverless features. - Querying large datasets interactively using Amazon Athena.
- Strong understanding of semantic modeling, including logical data models, virtual cubes, and centralized metric definitions (single source of truth). - Experience optimizing performance using query pushdown, caching, and aggregate awareness over platforms like Redshift and Athena. - Ability to integrate semantic layers with BI tools (QuickSight, Tableau, Power BI) and enforce row/column-level security aligned with governance frameworks.
- Deep working knowledge across key AWS Data & Analytics services, including: - Building large-scale data lake architectures on Amazon S3 and open table formats - Implementing governance and cataloging through AWS Lake Formation.
- Experience of working for customers/workloads in one of FSI,Retail,CPG domain. - Exposure to IaC tools like Terraform and to CI/CD tools - Familiarity with data virtualization (e.g., Amazon QuickSight,PowerBI, Tableau) and data governance tools (e.g., Collibra).
Your next step
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Already applied? Track this application
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.
If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!
Role : Associate Architect - Data (AWS + AtScale)
Experience : 5 - 13 Years
Location : Mumbai/Bangalore/Trivandrum
Must have Skills:
5+ years of experience in designing and implementing data warehouses and data lakes/lakehouse on AWS.
Hands-on experience with AtScale or similar semantic layer tools to enable governed, business-friendly data access across BI platforms.
Proven success working with globally distributed teams in collaborative delivery environments.
Deep working knowledge across key AWS Data & Analytics services, including:
Building large-scale data lake architectures on Amazon S3 and open table formats
Implementing governance and cataloging through AWS Lake Formation.
Developing ETL and metadata frameworks using AWS Glue.
Leveraging AWS Lambda for serverless data processing.
Running distributed data workloads on Amazon EMR.
Enabling real-time data pipelines with AWS Kinesis (Data Streams and Firehose).
Orchestrating pipelines using AWS Step Functions/Amazon MWAA/similar services.
Designing and optimizing schemas and query performance on Amazon Redshift, including Spectrum and Serverless features.
Querying large datasets interactively using Amazon Athena.
Managing operational databases using Amazon RDS across engines such as PostgreSQL, MySQL, and Aurora.
Integrating and migrating data using AWS DMS, Glue Connectors, EventBridge, SNS, and SQS.
Strong understanding of semantic modeling, including logical data models, virtual cubes, and centralized metric definitions (single source of truth).
Experience optimizing performance using query pushdown, caching, and aggregate awareness over platforms like Redshift and Athena.
Ability to integrate semantic layers with BI tools (QuickSight, Tableau, Power BI) and enforce row/column-level security aligned with governance frameworks.
Strong programming capability in Python and PySpark for large-scale data processing.
Proficiency in writing complex SQL queries, analytical functions, and performance tuning for large datasets.
Familiarity with NoSQL databases such as Amazon DynamoDB, MongoDB, or DocumentDB.
Strong understanding of partitioning, indexing, scaling approaches, and query optimization techniques.
Proven experience in architecting and implementing data pipelines using native AWS services in a modular and resilient manner.
Solid understanding of data modeling concepts, including dimensional, normalized, and lakehouse patterns.
Solution Architect- Associate or Data Engineer- Associate Certification.
Good to have skills:
Experience of working for customers/workloads in one of FSI,Retail,CPG domain.
Exposure to IaC tools like Terraform and to CI/CD tools
Familiarity with data virtualization (e.g., Amazon QuickSight,PowerBI, Tableau) and data governance tools (e.g., Collibra).
Managing security, monitoring, and compliance with AWS IAM, Secrets Manager, CloudWatch, CloudTrail, and KMS.
Experience with AI-assisted development tools such as GitHub Copilot, Amazon Kiro (or similar GenAI IDEs) for improving developer productivity, code generation, and pipeline acceleration
Exposure to Data Mesh architecture,Data Governance frameworks
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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IN KA Bengaluru
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