Job Title : Lead Data Architect ML & BI
Experience : 10 - 15 years
Role Overview :
Zinnobyte's Client is looking for a hands-on Lead Data Architect to design and build the next-generation data, machine learning, and business intelligence platform for our HR, Payroll, and Benefits SaaS ecosystem. This is a builders role perfect for someone who thrives on writing code, deploying models, architecting pipelines, and enabling intelligent reporting systems for real-world users.
You will work closely with product and engineering teams to drive a data-first culture by delivering clean, well-modeled, governed, and actionable data to power automation, analytics, and decision-making across the platform.
Key Responsibilities :
1) Data Engineering & Architecture :
- Design and implement scalable ETL / ELT pipelines for batch and real-time data processing.
- Architect data lakes, marts, and warehouses using best-in-class modeling principles (e.g., star schema, dimensional modeling).
- Maintain and optimize multi-tenant data access and ensure system security, masking, and role-based access controls (RBAC).
2) BI and Reporting Systems :
Own the architecture and delivery of reporting frameworks that serve both internal users and external customers.Enable scheduled, ad hoc, and role-based reporting via embedded dashboards or APIs.Define core business metrics, governance rules, and source-of-truth data structures.3) ML Model Development :
Build, deploy, and monitor machine learning models for use cases like anomaly detection, predictions, and intelligent assistants.Collaborate with product teams to translate real-world problems into deployable ML solutions (e.g., using scikit-learn, XGBoost, or LLMs).Implement MLOps practices for model training pipelines, version control, and performance monitoring.4) Data Governance & Compliance :
Define and implement data quality checks, profiling, validation, and lineage tracking.Ensure compliance with PII / PHI regulations (HIPAA, ISO 27701), working closely with security and infrastructure teams.Guide tagging, cataloging, and metadata strategies to support data discoverability and trust.Required Skills & Qualifications :
Education : B.Tech / M.Tech in Computer Science, Data Science, or related field.Experience : 10+ years in data engineering or architecture, including 3+ years delivering ML or BI solutions.Expert in Python, SQL, and data engineering frameworks (e.g., Airflow, dbt, custom pipelines).Deep knowledge of PostgreSQL, data warehousing, and multi-tenant SaaS data design.Hands-on experience building and deploying machine learning models in production environments.Experience with BI / reporting tools (Metabase, Superset, Looker, or embedded dashboards).Strong understanding of data security, governance, and compliance best practices.Familiarity with AWS data stack (e.g., S3, RDS, Glue, Redshift, Lambda) is preferred.Nice to Have :
Exposure to LLM / AI frameworks (e.g., LangChain, RAG pipelines, vector databases).Experience with event-driven architecture, messaging systems (Kafka, RabbitMQ).Prior experience with multi-tenant data platforms in SaaS or HR / payroll domain.Familiarity with observability tools (e.g., Prometheus, Grafana, OpenTelemetry).(ref : hirist.tech)
