Data Architect

7 days ago

Hyderabad, India ADP Full time

Data Architect
Experience Level: 12+ Years
Location: Hyderabad
Employment Type: Full-time

Position Overview
We are seeking a seasoned Data Architect to lead the design and evolution of our next-generation ETL platform supporting multiple products. You'll architect scalable data solutions processing millions of records across multi-tenant environments while ensuring data quality and governance.

Key Responsibilities

Platform Architecture & Design
Design and optimize Databricks-based ETL architectures for enterprise-scale data processing
Architect data warehouse solutions for multiple products
Design metadata-driven ETL frameworks with configurable processing pipelines

Data Engineering Leadership
Implement MPP architectures for high-volume data loads
Create reusable ETL patterns and skeleton frameworks across product lines
Architect Delta Lake and Redshift integration patterns for hybrid data storage
Design data quality frameworks with automated validation and monitoring

Technical Strategy
Define data modelling standards for dimensional and transactional data structures
Architect region-specific deployment patterns (EMEA, Americas)
Design secret management and connection pooling strategies

Governance & Quality
Establish data lineage and audit trail architectures
Design client data segregation and security models
Implement comprehensive data quality dashboards and monitoring
Create disaster recovery and data retention strategies

Required Qualifications

Technical Expertise
12+ years in data architecture with enterprise ETL platforms
Expert-level experience with Databricks, Apache Spark, and PySpark
Advanced knowledge of AWS services (S3, Redshift, IAM)
Proficiency in Delta Lake, data lakehouse architectures
Strong SQL optimization and database design skills

Platform Experience
Hands-on experience with multi-tenant SaaS data architectures
Knowledge of data quality frameworks and validation engines
Experience with notebook-based orchestration and workflow management

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