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Hiring for Data Architect SME

Hi
 
 
Please find the job description below and let me know your interest.
 

Title: Data Architect SME

Duration: Contract

Work Location: Remote

 

Client is looking for a Data Architect SME resource

Note:- Candidate should have Hands on experience in Databricks +AWS, Data Modeling & Design, PySpark Scripts, SQL Knowledge, Unity Catalog and Security Design, Identity federation, Auditing and Observability system tables/API/external tools, Access control / Governance in UC, External locations & storage credentials, Personal tokens & service principals, Metastore & unity catalog concepts, Interactive vs production workflows, Policies & entitlements, Compute types (incl. UC & non UC, scaling, optimization)

 

Data Strategy & Architecture Development

  • Define and implement the data architecture and data strategy aligned with business goals.
  • Design scalable, cost-effective, and high-performance data solutions using Databricks on AWS, Azure, or GCP.
  • Establish best practices for Lakehouse Architecture and Delta Lake for optimized data storage, processing, and analytics.

 

Data Engineering & Integration Architect ETL/ELT pipelines leveraging Databricks Spark, Delta Live Tables, and Databricks Workflows.

  • Optimize data ingestion from sources like Oracle Fusion Middleware, Web Methods, MuleSoft, and Informatica into Databricks.
  • Ensure real-time and batch data processing with Apache Spark and Delta Lake.
  • Work on data integration strategies, ensuring seamless connectivity with enterprise systems (e.g., Salesforce, SAP, ERP, CRM).

 

Data Governance, Security & Compliance Implement data governance frameworks leveraging Unity Catalog for data lineage, metadata management, and access control.

  • Ensure compliance with HIPAA, GDPR, and other regulatory standards in life sciences.
  • Define RBAC (Role-Based Access Control) and enforce data security best practices using Databricks SQL and access policies.
  • Enable data stewardship and ensure data cataloging for self-service data democratization.

 

Performance Optimization & Cost Management Optimize Databricks compute clusters (DBU usage) for cost efficiency and performance tuning.

  • Define and implement query optimization techniques using Photon Engine, Adaptive Query Execution (AQE), and caching strategies.
  • Monitor Databricks workspace health, job performance, and cost analytics.

 

AI/ML Enablement & Advanced Analytics Design and support ML pipelines leveraging Databricks ML flow for model tracking and deployment.

  • Enable AI-driven analytics in genomics, drug discovery, and clinical data processing.
  • Collaborate with data scientists to operationalize AI/ML models in Databricks.

 

Collaboration & Stakeholder Alignment Work with business teams, data engineers, AI/ML teams, and IT leadership to align data strategy with enterprise goals.

  • Collaborate with platform vendors (Databricks, AWS, Azure, GCP, Informatica, Oracle, MuleSoft) for solution architecture and support.
  • Provide technical leadership, conduct PoCs, and drive Databricks adoption across the organization.

 

Data Democratization & Self-Service Enablement Implement data sharing frameworks for self-service analytics using Databricks SQL and BI integrations (Power BI, Tableau).

  • Promote data literacy and empower business users with self-service analytics.
  • Establish data lineage and cataloging to improve data discoverability and governance.

 

Migration & Modernization Lead the migration of legacy data platforms (Informatica, Oracle, Hadoop, etc.) to Databricks Lakehouse.

  • Design a roadmap for cloud modernization, ensuring seamless data transition with minimal disruption.

 

Mandatory Key Skills:

Databricks & Spark Expertise Strong knowledge of Databricks Lakehouse architecture (Delta Lake, Unity Catalog, Photon Engine).

  • Expertise in Apache Spark (PySpark, Scala, SQL) for large-scale data processing.
  • Experience with Databricks SQL and Delta Live Tables (DLT) for real-time and batch processing.
  • Understanding of Databricks Workflows, Job Clusters, and Task Orchestration.

 

Cloud & Infrastructure Knowledge Hands-on experience with Databricks on AWS, Azure, or GCP (preferred AWS Databricks).

  • Strong understanding of cloud storage (ADLS, S3, GCS) and cloud networking (VPC, IAM, Private Link).
  • Experience with Infrastructure as Code (Terraform, ARM, CloudFormation) for Databricks setup.

 

Data Modeling & Architecture Expertise in data modeling (Dimensional, Star Schema, Snowflake, Data Vault).

  • Experience with Lakehouse, Data Mesh, and Data Fabric architectures.
  • Knowledge of data partitioning, indexing, caching, and query optimization.

 

ETL/ELT & Data Integration Experience designing scalable ETL/ELT pipelines using Databricks, Informatica, MuleSoft, or Apache NiFi.

  • Strong knowledge of batch and streaming ingestion (Kafka, Kinesis, Event Hubs, Auto Loader).
  • Expertise in Delta Lake & Change Data Capture (CDC) for real-time updates.

 

Data Governance & Security Deep understanding of Unity Catalog, RBAC, and ABAC for data access control.

  • Experience with data lineage, metadata management, and compliance (HIPAA, GDPR, SOC 2).
  • Strong skills in data encryption, masking, and role-based access control (RBAC).

 

Performance Optimization & Cost Management Ability to optimize Databricks clusters (DBU usage, Auto Scaling, Photon Engine) for cost efficiency.

  • Knowledge of query tuning, caching, and performance profiling.
  • Experience monitoring Databricks job performance using Ganglia, CloudWatch, or Azure Monitor.

 

AI/ML & Advanced Analytics

  • Experience integrating Databricks ML flow for model tracking and deployment.
  • Knowledge of AI-driven analytics, Genomics, and Drug Discovery in life sciences
 
 

Thanks & Regards,

 

Abhishek Kumar

 

SPAR Information Systems

(an E-verify Company)

www.sparinfosys.com

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