AWS Data Architect

• 🔹 AWS Data Architect | Wealth Management | Fulltime
• 📍 New York, NY / Fort Mill, South Carolina (Hybrid)

• Job Title: AWS Data Architect (Hands-on)
• Location: New York, NY/ Fort Mill, SC (Hybrid)
• Employment Type: Full-time
• Experience Required: 15+ years

Role Overview

• We are looking for a highly skilled, hands-on AWS Data Architect to design and implement enterprise-grade data platforms for a leading financial services client. This role requires deep technical expertise, strong architectural ownership, and the ability to build, optimize, and scale modern data ecosystems on AWS.
• The ideal candidate will not only define architecture but also actively design, code, and troubleshoot pipelines and data systems.

Key Responsibilities

• 1. End-to-End Data Architecture (Hands-on)
• Design and implement scalable AWS-based data platforms including data lakes, lakehouses, and warehouses.
• Build robust data pipelines (batch & real-time) from scratch.
• Define and enforce data architecture standards, frameworks, and governance models.
• Create logical and physical data models (OLTP, OLAP, dimensional modeling).

• 2. AWS Data Stack (Deep Expertise Required)
• Hands-on experience designing and implementing solutions using:
• Storage & Warehousing:
• Amazon S3, Redshift, Aurora, RDS
• Data Processing & ETL:
• AWS Glue (Spark), EMR (PySpark), Lambda
• Streaming & Real-time:
• Kinesis (Streams, Firehose), MSK (Kafka)
• Query & Analytics:
• Athena, Redshift Spectrum
• Orchestration:
• Step Functions, Airflow (MWAA preferred)
• Governance & Security:
• Lake Formation, IAM, KMS, Secrets Manager

• 3. Advanced Data Engineering (Must be Hands-on)
• Develop complex ETL/ELT pipelines using Python, PySpark, SQL.
• Optimize large-scale distributed data processing systems.
• Implement CDC (Change Data Capture) and near real-time ingestion pipelines.
• Work with structured, semi-structured, and unstructured data.

• 4. Performance & Cost Optimization
• Tune Redshift/Spark workloads (partitioning, compression, distribution keys).
• Optimize storage & compute usage for cost efficiency.
• Troubleshoot performance bottlenecks across pipelines.

• 5. Financial Domain Data Expertise
• Design solutions aligned to regulatory, compliance, and audit requirements.
• Handle sensitive financial data (PII, PCI) securely.
• Ensure adherence to data governance, lineage, and auditability standards.

• 6. DevOps & Automation
• Implement Infrastructure as Code using Terraform / CloudFormation.
• Build CI/CD pipelines for data workflows.
• Automate deployments, monitoring, and alerting.

• 7. Collaboration & Leadership
• Work closely with data engineers, analysts, risk teams, and business stakeholders.
• Provide technical leadership and mentorship.
• Drive architectural decisions and best practices across teams.

Required Qualifications

Experience

• 15+ years in data engineering / data architecture
• 6–8+ years of strong AWS data architecture experience
• Proven track record of designing enterprise data platforms at scale

• Technical Skills (Must Have)
• Strong programming: Python (mandatory), PySpark, SQL
• Deep hands-on with Spark, distributed processing frameworks
• Expertise in data warehousing & modeling concepts
• Experience with real-time and streaming architectures
• Hands-on experience with CI/CD + DevOps pipelines

• AWS Expertise
• Strong knowledge of AWS Well-Architected Framework
• Experience building serverless data architectures
• Security best practices in financial cloud environments

• Preferred Qualifications
• AWS Certifications:
• AWS Certified Solutions Architect (Professional preferred)
• AWS Certified Data Analytics – Specialty
• Experience with:
• Snowflake / Databricks (nice to have)
• Data quality frameworks (Great Expectations, Deequ)
• Data catalog tools (Glue Catalog, Collibra, Alation)
• Exposure to risk, compliance, or financial analytics systems

• Soft Skills
• Strong problem-solving & analytical mindset
• Excellent communication with technical & business stakeholders
• Ability to work in a hybrid and cross-functional setup
• Leadership mindset with hands-on contribution

• What Makes You a Great Fit
• You don’t just design—you build and optimize.
• You have experience handling highly regulated financial data systems.
• You can operate at architect level while staying deeply technical.