Enterprise Data Architect

Job summary

Define and lead secure, scalable Hadoop and Big Data architectures for analytics, reporting, and AI, including ingestion, batch and streaming processing, data lakes, governance, and modernization. Provide technical leadership across delivery and production readiness, optimize performance and reliability, guide teams, and support client-facing solutioning and architecture standards.

Job details

Skills Required: Must to Have: • 14+ years of experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization. • Strong hands-on expertise in Hadoop, HDFS, YARN, Hive, Spark, PySpark, Kafka, SQL, Python, Java, and Scala. • Experience designing and implementing large-scale Big Data and Data Lake architectures supporting analytics, reporting, and AI workloads. • Strong understanding of Hadoop platform architecture, including HDFS, YARN, high availability, cluster management, workload optimization, and scalability. • 14+ years of experience in Enterprise Data Architecture, Hadoop Ecosystem, Big Data Engineering, and Data Platform Modernization. • Strong hands-on expertise in Hadoop, HDFS, YARN, Hive, Spark, PySpark, Kafka, SQL, Python, Java, and Scala. • Experience designing and implementing large-scale Big Data and Data Lake architectures supporting analytics, reporting, and AI workloads. • Strong understanding of Hadoop platform architecture, including HDFS, YARN, high availability, cluster management, workload optimization, and scalability. • Expertise in batch and distributed data processing using Spark, Hive, HBase, and MapReduce frameworks. • Experience building data ingestion and streaming solutions using Kafka and Hadoop ecosystem tools. • Strong knowledge of Data Engineering practices, including ETL/ELT, data integration, data quality, metadata management, lineage, observability, and DataOps. • Experience with Data Lake, Data Warehousing, Enterprise Data Models, Master Data, and Data Governance frameworks. • Strong understanding of security and governance controls, including Kerberos, Ranger, encryption, privacy, auditability, compliance, and controlled data access. • Proven experience in architecture definition, HLD/LLD creation, migration planning, technical governance, production readiness, and performance optimization. • Experience supporting platform modernization, cloud adoption, solutioning, effort estimation, and client-facing technical discussions. • Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements. • Preferred certifications in Hadoop, Spark, Cloud Data Engineering, Enterprise Architecture, Data Management, Security, or Big Data Platforms. Roles and Responsibilities: • Engage with business and technology stakeholders to understand business objectives, data platform requirements, and modernization goals. • Define end-to-end architecture for Hadoop and Big Data platforms supporting analytics, reporting, and AI workloads. • Design scalable, secure, and high-performance Hadoop ecosystems using HDFS, YARN, Spark, Kafka, Hive, and related technologies. • Architect data ingestion, batch processing, streaming, and data lake solutions for enterprise-scale environments. • Define data models, data lake zones, governance frameworks, metadata management, lineage, and security standards. • Lead Hadoop modernization, migration, and platform optimization initiatives to improve performance, scalability, and operational efficiency. • Establish architecture standards, reusable frameworks, engineering best practices, and DataOps operating models. • Provide technical leadership across solution design, implementation, testing, migration, deployment, and production support activities. • Conduct architecture reviews, identify risks and dependencies, and guide teams on mitigation strategies and best practices. • Drive performance tuning, capacity planning, reliability improvements, and infrastructure cost optimization. • Collaborate with data engineers, platform teams, architects, vendors, and client stakeholders to deliver enterprise data solutions. • Support solutioning, RFP responses, effort estimation, technical presentations, and client workshops. • Mentor architects and engineers and contribute to hiring, capability development, and knowledge-sharing initiatives. Develop reusable accelerators, reference architectures, implementation frameworks, and technical best practices for Big Data platforms

What you’ll do

Define and lead secure, scalable Hadoop and Big Data architectures for analytics, reporting, and AI, including ingestion, batch and streaming processing, data lakes, governance, and modernization. Provide technical leadership across delivery and production readiness, optimize performance and reliability, guide teams, and support client-facing solutioning and architecture standards.

Requirements

Requires 14+ years of experience in enterprise data architecture, Hadoop, Big Data engineering, and data platform modernization, with hands-on expertise in Hadoop ecosystem technologies, programming languages, and distributed processing. Candidates should also bring strong data engineering, governance, security, architecture, migration, and performance optimization experience; Hadoop, Spark, cloud data engineering, architecture, data management, security, or Big Data certifications are preferred.

Listed skills

• SQL · Preferred
• Java · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Enterprise Data Architecture
• Hadoop
• HDFS
• YARN
• Hive
• Spark
• PySpark
• Kafka
• SQL
• Python
• Java
• Scala
• Big Data Engineering
• Data Lake Architecture
• Data Governance
• DataOps

Job areas

• Data & Analytics
• Technology
• Software
• Consulting
• Management & Leadership

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