Sr. Enterprise Architect - Data Engineering

We are looking for a highly experienced Senior Enterprise Architect specializing in Data Engineering to join a fast-paced, client-facing engagement. This is a senior, hands‑on leadership role for someone who can architect enterprise‑grade data solutions, engage directly with clients, and drive delivery through offshore teams. This is an on‑site role, with a preference for candidates based in New York or New Jersey. About the Role What You'll Be Doing Designing, building, and optimizing scalable ETL/ELT pipelines that integrate data from multiple sources into a cloud‑native AWS architecture Leading data platform architecture decisions, including real‑time and near‑real‑time data layers Driving Medallion Architecture implementation and enforcing data quality standards using frameworks like Databricks DQX Implementing event‑driven data workloads using Kafka, JSON payloads, and Python‑based API design Collaborating directly with client stakeholders to gather requirements and translate them into robust data solutions Mentoring and managing offshore engineering teams to ensure quality delivery Establishing data modeling standards, data lineage practices, and canonical data model frameworks Monitoring, troubleshooting, and continuously improving pipeline performance Documenting architecture, engineering processes, and best practices for team knowledge sharing Requirements 20+ years of overall technology experience 8+ years of deep, hands‑on experience in data engineering, analytics, or data platform architecture Minimum 8 years working with Databricks, Kafka, and cloud‑native application development Prior experience in the Insurance domain is mandatory Qualifications Bachelor's degree in Engineering or MCA from a reputed institution Databricks certification is a plus Required Skills Hands‑on Databricks expertise: Python, PySpark, YAML, API design, Delta Lake, schema evolution, and transactional data patterns Expert‑level SQL including query optimization and large‑scale data processing Strong experience with Databricks DQX or equivalent data quality frameworks Proven ability to design and build OLTP and near‑real‑time data layers Kafka event‑driven architecture: JSON payloads, Python, and API integration Cloud‑native data architecture on AWS (storage, compute, and data services) Data modeling for both analytical and OLTP‑style workloads Experience with SQL and NoSQL databases Familiarity with data governance frameworks and data lineage practices #J-18808-Ljbffr Reliance Resourcing Ltd