Technical Architect-Analytics

Job Title: Technical Architect - Analytics

Location: Gurgaon Or Bangalore - Hybrid India

Employment Type: Full-Time

Simpplr is the leading comprehensive modern intranet platform that helps companies connect and engage employees across the enterprise. Organizations use our forward-looking, adaptable products to deliver personalized experiences that inspire and engage their employees. Simpplr was built to help businesses not only create an immersive and inspiring digital workplace but also to reinforce their unique culture. We aim to break the barriers of traditional work environments to deliver a better workplace, anywhere.

Trusted by more than 700+ leading brands, including Penske, Snowflake, Moderna, Eurostar, and AAA, our customers are achieving measurable improvements in employee engagement, productivity, and accelerated business performance.

Simpplr is headquartered in Silicon Valley, CA with offices in UK, Canada, and India, and is backed by Sapphire Ventures, Norwest Venture Partners, Salesforce Ventures, and Tola Capital.

We are looking for a hands-on Technical Architect - Analytics who will be responsible for designing, developing, and optimizing our data and analytics architecture. You will play a critical role in defining the data strategy, designing scalable data pipelines, and implementing best practices for real-time and batch analytics solutions. This role requires a strong technical leader who is passionate about data engineering, analytics, and driving data-driven decision-making across the organization.

Key Responsibilities

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

What Makes You a Great Fit for Us

• Experience: 8+ years of experience in data architecture, analytics, and big data processing.
• Proven Track Record: Experience designing and implementing end-to-end data platforms for high-scale applications.
• Strong Data Engineering Background: Expertise in ETL/ELT pipelines, data modeling, data warehousing, and stream processing.
• Analytics Reporting Expertise: Experience working with BI tools, data visualization, and reporting platforms.
• Deep Knowledge of Modern Data Technologies:
• 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.
• Microservices Event-Driven Architecture: Understanding of real-time event processing architectures.
• Strategic Thinking: Ability to design and implement long-term data strategies aligned with business goals.
• Problem-Solving Optimization: Strong analytical skills with a deep understanding of performance tuning for large-scale data systems.
• Visionary Leadership: Ability to think strategically and drive engineering excellence within the team.
• Communication Skills: Strong interpersonal and communication skills to collaborate effectively across teams.
• Attention to Detail: An eye for detail with the ability to translate ideas into tangible, impactful outcomes.
• Agility: Comfortable managing and delivering work in a fast-paced, dynamic environment.

Preferred Skills (Good to Have)

• 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