AWS Data Architect

Employment Type: Full-time Experience Required: 14-20 years About Incedo Website: LinkedIn page: Incedo Inc. is a high-growth Digital, Data and AI Transformation Specialist firm headquartered in New Jersey. We are a long-term strategy execution partner for Fortune 500 enterprises, operating at the intersection of business and technology across Banking & Payments, Wealth Management, Telecom, Hi-Tech, and Life Sciences. We are building Incedo 4.0 - an AI-native, execution-focused, founder-led organization designed for scale, speed, and long-term impact. Incedo delivers ROI from AI @ Scale through the "Power of 3": Engineering & Operations excellence Why Join Us At Incedo, you will be part of a high-growth environment where innovation, collaboration, and customer-centricity are at the core of everything we do. This role offers significant visibility with senior leadership, an entrepreneurial culture, and the opportunity to build a long-term career in enterprise services sales at one of the fastest-growing Digital, Data and AI transformation firms 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: Orchestration: Step Functions, Airflow (MWAA preferred) Governance & Security: Lake Formation, IAM, KMS, Secrets Manager 3. Advanced Data Engineering (Must be Hands-on) 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. 5. Financial Domain Data Expertise Design solutions aligned to regulatory, compliance, and audit requirements . 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. 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 stakeholdersAbility 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 . #J-18808-Ljbffr Incedo Inc.