ARCHITECT - DATA ANALYTICS

Job Summary

An accomplished technology leader with 8+ years of experience in architecting and delivering scalable data-driven systems. This role oversees the design of data subsystems, provides strategic technical direction, and leads projects of significant organizational impact. The individual will engage directly with customers in high-level discussions and guide technical teams in modern data engineering practices, BI strategy, and advanced analytics across cloud platforms. Brings an innovation-first mindset and deep hands-on experience in data architecture, pipelines, visualization, and AI/ML readiness.

Key Responsibilities

• Own the architecture and design of scalable data engineering subsystems and cloud-native analytics solutions.
• Lead cross-functional teams on high-profile projects, making technical trade-off decisions that balance performance, cost, and delivery timelines.
• Engage with customers in technical forums to represent the organization as a thought leader and trusted advisor.
• Create data ingestion, transformation, and enrichment pipelines using ETL/ELT best practices.
• Drive the creation and automation of dashboards, reports, and self-service BI layers.
• Evaluate and integrate emerging technologies to improve platform capabilities and decision intelligence.
• Mentor senior engineers and architects, and foster a data-driven culture within the organization.

Education & Experience

• Bachelor's or Master's degree in Engineering, Computer Science, or equivalent (B.E./B.Tech/MCA)
• 8+ years of experience in data engineering, BI, and analytics leadership roles

Core Competencies

• Data Engineering Expertise:
• Data warehousing, big data pipelines, stream processing
• Handling structured/unstructured data and real-time ingestion
• Cloud & Platform Skills:
• Hands-on experience with AWS, Azure, GCP
• Cloud-native analytics and scalable storage systems
• Tools & Technologies:
• Data & Storage: MongoDB, Hive, HBase, ElasticSearch
• Visualization: Tableau, Power BI, QlikView
• Compute & Processing: Spark (MLlib), Kafka
• Programming & Querying:
• Languages: Python, Scala, SQL, R
• Frameworks: Spark, Hadoop, REST APIs

Specializations

• Data Warehousing (DWH)
• Big Data Engineering
• Edge Analytics & Real-Time Processing
• Data Architecture & BI Platform Design