Test - AWS Redshift Data Architect

CitiusTech

Dallas, TX, United States

about 2 months ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

3 years minimum

Working hours

Regular working hours

Job source

indeed.com

Tech stack

Amazon Web Services Amazon S3 Audit Trail Code Review Data Architecture Data Validation Data Governance Extract Transform Load (ETL) Data Migration IBM InfoSphere DataStage Identity and Access Management Meta-Data Management

+6 more

Performance Tuning Tableau (Software) Teradata SQL Cloudwatch Alteryx Amazon Redshift

Job description

Collaborate with ETL, BI, and ML teams to ensure seamless integration with DataStage, Alteryx, Tableau, and SageMaker.
Oversee schema migration from Teradata using AWS SCT and DMS tools.
Drive performance tuning of Redshift queries, workloads, and resource management.
Implement security best practices, including IAM roles, encryption, and access control.
Support data validation and reconciliation efforts.
Provide technical leadership and guidance to data engineers and developers.
Participate in code reviews, design sessions, and architecture governance forums.
Collaborate with stakeholders to define and implement data governance, lineage, and metadata strategies.

Requirements

Do you have experience in Stakeholder relationship building?, * Experience in data architecture, with at least 3 years on AWS Redshift.

Strong expertise in Redshift internals, Spectrum, RA3 nodes, and concurrency scaling.
Proficient in SQL performance tuning, workload management.
Experience with AWS services: S3, DataZone, IAM, CloudWatch, CloudTrail.
Familiarity with ETL tools (DataStage, Alteryx) and BI tools (Tableau).
Hands-on experience with schema conversion tools (SCT) and data migration strategies.
Knowledge of data governance, cataloging, and metadata management.
Excellent communication and stakeholder management skills, * Lead the design and architecture of AWS Redshift clusters, including sizing, workload management, and security.
Define and implement data modeling strategies aligned with business and analytical requirements.