Role Summary

The AWS Lakehouse Architect owns the end-to-end design of a modern, open-format lakehouse on AWS. The role defines target-state architecture, data modelling standards, governance and security patterns, and guides engineering teams through build, migration, and optimisation. The Senior Manager additionally leads client/stakeholder relationships, solution strategy, and practice growth.

Key Responsibilities

Define lakehouse reference architecture across ingestion, storage, processing, serving, and consumption layers using S3, AWS Glue, Lake Formation, EMR, Athena, Redshift, and open table formats (Apache Iceberg / Delta Lake / Hudi).

Design medallion (bronze/silver/gold) or equivalent layering, partitioning, compaction, and schema-evolution strategies.

Establish data governance: catalogue, lineage, fine-grained access control (Lake Formation, IAM, tag-based access), data quality, and data classification.

Lead migration roadmaps from legacy warehouses / Hadoop / on-prem platforms (Teradata, Oracle, Cloudera, etc.) to AWS.

Define non-functional requirements - performance, scalability, cost, availability, DR, and security (KMS, VPC design, Private Link).

Review designs and code produced by data, streaming, and platform teams; enforce standards and best practices.

Partner with MLOps and AI teams to ensure the lakehouse serves feature stores, ML training, and GenAI/RAG use cases.

Produce architecture artefacts: HLD/LLD, ADRs, data models, and cost estimates.

Additional Senior Manager

Own overall solution strategy and technical delivery across the programme; act as the principal technical advisor to client leadership.

Lead pre-sales,



proposals, solution sizing, and effort/cost estimation.

Manage and mentor architects and engineering leads; build reusable accelerators and practice IP.

Manage risk, escalations, and governance forums (architecture review boards, steering committees).

Additional Manager

Own architecture for one or more workstreams; lead day-to-day technical direction for engineering squads.

Translate business requirements into technical designs and backlog epics.

Required Skills

Deep hands-on expertise in AWS data services: S3, Glue (ETL, Catalog, Data Quality), Lake Formation, EMR / EMR Serverless, Athena, Redshift (incl. Spectrum & Serverless), DMS, Step Functions.

Strong knowledge of open table formats (Iceberg preferred), Parquet/ORC, and distributed processing with Apache Spark.

Data modelling (dimensional, Data Vault, domain-oriented / data mesh concepts).

Strong SQL and Python/PySpark; familiarity with dbt.

Infrastructure-as-Code (Terraform / AWS CDK / Cloud Formation) and CI/CD for data platforms.

Data security and compliance patterns (encryption, masking, PII handling, audit).

Preferred

AWS Certified Solutions Architect Skilled and/or AWS Certified Data Engineer Associate.

Exposure to Databricks on AWS or Snowflake in hybrid architectures.

Experience in BFSI, Telecom, Retail, or Healthcare data platforms.

TOGAF or equivalent architecture framework knowledge.

Education

B.E./B. Tech/MCA/M. Tech or equivalent in Computer Science, IT, or related field.
Additional Information: SPOC - Shalini ()
Mandatory Skills - Under JD
Nice to have skills - Under JD
Clean Room Project - No

📌 AWS Lakehouse ArchitecT (India)
🏢 Objectwin Technology India
📍 India