
Lead Data Architect
1 week ago
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)
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