Job Description
We are seeking a mid-level Data Architect with strong AWS skills to build and maintain data pipelines that support Golden Record creation(CDP) and Master Data Management (MDM). This role focuses on identity resolution, data quality, and delivering trusted, unified data assets across the organization. Responsibilities include developing data models and supporting analytics initiatives. The candidate will collaborate with cross-functional teams to ensure data systems are aligned with organizational needs and industry's best practices.
This position will be based in Atlanta, GA or Tampa, FL.
What You'll Do: - Define and own the conceptual, logical, and physical data models; establish standards for modeling, metadata, lineage, retention, and quality across platforms.
- Design and steward Golden Records (e.g., Customer, Leads) within an MDM framework; set survivorship, standardization, and enrichment rules.
- Specify identity resolution approaches (deterministic/probabilistic matching, deduplication) and guide implementation across domains.
- Define reference architectures and patterns for scalable AWS data pipelines and services (Glue, Lambda, Step Functions, EMR/Spark, S3, Athena, Redshift); drive cost, performance, and reliability best practices.
- Architect incremental, real time, and event driven data processing (Kinesis, SNS/SQS), ensuring resilient, observable pipelines.
- Oversee CI/CD and IaC (CloudFormation, Terraform) for data workloads and infrastructure templates.
- Design semantic layers and curated datasets for business consumption to enable self-service analytics and executive dashboards using BI tools like Tableau, PowerBI.
- Establish enterprise data quality frameworks (validation, profiling, monitoring) and SLAs for trusted datasets.
- Partner with Infrastructure and Business on data privacy, access controls, encryption, and auditability (aligned with governance tools like Glue Data Catalog, Collibra, Alation).
- Translate business requirements into target state architectures and solution designs; review solution/tech designs produced by engineering teams.
- Guide troubleshooting and optimization of production data systems; champion operability and SRE practices for data pipelines.
- Document standards, patterns, and architecture decisions; mentor engineers and analysts on data architecture practices.
What We're Looking For: - Bachelor's or Master's degree in Computer Science, Data Science, or related field (or equivalent experience).
- Deep expertise designing and governing enterprise data architectures, including MDM, identity resolution, data quality, and survivorship rules.
- Hands on AWS experience across data services (Glue, Lambda, Step Functions, S3, Athena, Redshift, EMR/Spark).
- Strong SQL, with emphasis on PostgreSQL; proficiency in Python, C#, and/or Spark for data engineering workloads.
- Experience with ETL/ELT design, Spark transformations, and distributed data processing.
- Proven ability to collaborate cross functionally and operate effectively in an on site team environment.
- Experience with CDP platforms and event driven cloud architectures.
- Proven experience designing data solutions that support BI and dashboarding tools.
- Familiarity with data governance/catalog solutions (Glue Data Catalog, Collibra, Alation).
- CI/CD and IaC tools (CloudFormation, Terraform).
- Experience with our data stack is a plus: We use PostgreSQL, RedPoint, MySQL, and Microsoft SQL Server.
- Analytical problem solving and systems thinking.
- Clear communication across technical and business stakeholders; ability to translate between business outcomes and architectural choices.
- Proactive, detail oriented approach with high standards for data accuracy and reliability.
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