Technical Architect-Analytics

Summary

Join Simpplr as a Technical Architect - Analytics and play a critical role in designing, developing, and optimizing our data and analytics architecture. You will define the data strategy, design scalable data pipelines, and implement best practices for real-time and batch analytics solutions. This hands-on role requires a strong technical leader passionate about data engineering, analytics, and driving data-driven decision-making. You will collaborate with various teams, ensuring data security and compliance. The position offers a hybrid work model and is based in Gurgaon or Bangalore, India.

Requirements

• 8+ years of experience in data architecture, analytics, and big data processing
• Experience designing and implementing end-to-end data platforms for high-scale applications
• Expertise in ETL/ELT pipelines, data modeling, data warehousing, and stream processing
• Experience working with BI tools, data visualization, and reporting platforms
• Big Data & Analytics: Spark, Kafka, Hadoop, Druid, ClickHouse, Presto, Snowflake, Redshift, BigQuery
• Databases: PostgreSQL, MongoDB, Cassandra, ElasticSearch
• Cloud Platforms: AWS, GCP, Azure (experience with cloud data warehouses like AWS Redshift, Snowflake is a plus)
• Programming & Scripting: Python, SQL, Java, Scala
• Understanding of real-time event processing architectures
• Ability to design and implement long-term data strategies aligned with business goals
• Strong analytical skills with a deep understanding of performance tuning for large-scale data systems
• Ability to think strategically and drive engineering excellence within the team
• Strong interpersonal and communication skills to collaborate effectively across teams
• An eye for detail with the ability to translate ideas into tangible, impactful outcomes
• Comfortable managing and delivering work in a fast-paced, dynamic environment

Responsibilities

• Define and own the architecture for data processing, analytics, and reporting systems, ensuring scalability, reliability, and performance
• Design and implement highly efficient, scalable, and reliable data pipelines for structured and unstructured data
• Architect and optimize data processing workflows for batch, real-time, and streaming analytics
• Work closely with Product Managers, Data Scientists, Analysts, and Software Engineers to translate business requirements into scalable data architectures
• Stay ahead of industry trends, introduce modern data technologies, and drive best practices in data architecture, governance, and security
• Review code, enforce data engineering best practices, and mentor engineers to build a high-performance analytics team
• Ensure data security, integrity, and compliance with regulations (GDPR, CCPA, etc.)
• Identify performance bottlenecks in data pipelines and analytics workloads, optimizing for cost, speed, and efficiency
• Lead cloud-based data platform initiatives, ensuring high availability, fault tolerance, and cost optimization

Preferred Qualifications

• Hands-on experience with AWS Public Cloud
• Experience with Machine Learning Pipelines and AI-driven analytics
• Hands-on experience with Kubernetes, Terraform, and Infrastructure-as-Code (IaC) for data platforms
• Certifications in AWS Data Analytics, Google Professional Data Engineer, or equivalent
• Experience with data security, encryption, and access control mechanisms
• Experience in Event/Data Streaming platforms
• Experience in risk management and compliance frameworks

Benefits

Hybrid work from home and office