AWS Data & Lakehouse Architect
Description
Hi
I have an urgent requirement with my client for AWS Data & Lakehouse Architect
Title: AWS Data & Lakehouse Architect
Location: Plano, TX
Work Model: Onsite, 3–4 days per week
Candidate Preference: Local candidates preferred
Type: C2C or 1099.
Interested can share resume at leo(@)elintpros(.)com
Role Type: Contract
Experience: Preferably 10+ years overall with strong recent hands-on AWS/Data Engineering architecture experience
Role Overview
TMNA is looking for an experienced AWS Data & Lakehouse Architect to support enterprise data modernization initiatives involving migration of legacy/on-premises data platforms to a modern AWS-based Data Lakehouse architecture using Databricks and Apache Spark.
The ideal candidate should combine strong architecture capabilities with hands-on engineering experience. This is not purely an advisory or high-level solution architect role. The candidate should be comfortable designing the target architecture as well as working directly with AWS services, Databricks, Spark, data pipelines, security configurations, performance optimization, and migration patterns.
Key Responsibilities
1. AWS Data & Cloud Architecture
· Design scalable, resilient, secure, and cost-effective enterprise data platforms on AWS.
· Define reference architectures for migration from on-premises data platforms to AWS Data Lake/Lakehouse.
· Architect AWS solutions leveraging services such as:
o Amazon S3
o IAM
o AWS Glue
o AWS Lake Formation
o Amazon Redshift
o Amazon RDS/Aurora
o AWS Lambda
o Amazon EC2
o Amazon VPC
o AWS KMS
o CloudWatch
o CloudTrail
o Secrets Manager
o AWS Step Functions
o Amazon EventBridge
· Define appropriate patterns for networking, security, data ingestion, storage, processing, consumption, and monitoring.
2. Databricks & Lakehouse Architecture
· Design and implement enterprise Databricks Lakehouse solutions on AWS.
· Strong hands-on experience with Databricks, Apache Spark, PySpark, SQL and Delta Lake.
· Design Bronze, Silver and Gold data-layer patterns based on workload requirements.
· Define scalable ingestion, transformation, orchestration, and data-serving patterns.
· Implement and optimize Delta tables, partitioning strategies, Spark workloads, cluster configurations, and large-scale ETL/ELT pipelines.
· Experience with Databricks Unity Catalog, governance, access controls, lineage, and workspace architecture is highly desirable.
Interested can share resume at leo(@)elintpros(.)com