Hi,
I hope this email finds you well.
My name is Shivam kumar and I am a Technical Recruiter from Empower
Professionals Inc. I came across your profile and wanted to reach out
regarding a "Databrick Architect-19161-1" role with one of our clients
based in "100% Remote". Please let me know if you are available in the
job market and interested in this role (see job description below) - if
so, we can connect and speak further.
I would need your updated resume to proceed and can give you a call as
soon as I have it.
Role- Databricks Architect
Location: 100% Remote
Duration: 12+ months
Must Have Skills –
Databricks +AWS
Data Modeling & Design
PySpark Scripts
SQL Knowledge
Data Integration
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
Meta store & Unity Catalog Concepts
Interactive vs production workflows
Policies & entitlements
Compute types (incl. UC & non-UC)
Key Skills:
Databricks & Spark:
Databricks Lakehouse, Delta Lake, Unity Catalog, Photon Engine.
Apache Spark (PySpark, Scala, SQL), Databricks SQL, Delta Live
Tables, Databricks Workflows.
Cloud Platforms:
Databricks on AWS (preferred), Azure, or GCP.
Cloud storage (S3, ADLS, GCS), VPC, IAM, Private Link.
Infrastructure as Code: Terraform, ARM, CloudFormation.
Data Modeling & Architecture:
Dimensional, Star Schema, Snowflake, Data Vault.
Experience with Lakehouse, Data Mesh, and Data Fabric architectures.
Data partitioning, indexing, caching, query optimization.
ETL/ELT & Integration:
ETL/ELT development with Databricks, Informatica, MuleSoft, Apache
tools.
Job description-
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, Meta store & unity catalog concepts, Interactive vs
production workflows, Policies & entitlements, Compute types (incl. UC &
non UC, scaling, optimization)
Key Responsibilities:
1. Data Strategy & Architecture Development
Define and implement scalable, cost-effective, and high-performance
data architecture aligned with business objectives.
Design Lakehouse solutions using Databricks on AWS, Azure, or GCP.
Establish best practices for Delta Lake and Lakehouse Architecture.
2. Data Engineering & Integration
Architect ETL/ELT pipelines using Databricks Spark, Delta Live
Tables (DLT), and Databricks Workflows.
Integrate data from sources like Oracle Fusion Middleware, Web
Methods, MuleSoft, Informatica.
Enable real-time and batch processing using Apache Spark and Delta
Lake.
Ensure seamless connectivity with enterprise platforms (Salesforce,
SAP, ERP, CRM).
3. Data Governance, Security & Compliance
Implement governance frameworks using Unity Catalog for lineage,
metadata, and access control.
Ensure HIPAA, GDPR, and life sciences regulatory compliance.
Define and manage RBAC, Databricks SQL security, and access
policies.
Enable self-service data stewardship and democratization.
4. Performance Optimization & Cost Management
Optimize Databricks compute clusters (DBU usage) for cost
efficiency.
Leverage Photon Engine, Adaptive Query Execution (AQE), and caching
for performance tuning.
Monitor workspace health, job efficiency, and cost analytics.
5. AI/ML Enablement & Advanced Analytics
Design and manage ML pipelines using Databricks MLflow.
Support AI-driven analytics in genomics, drug discovery, and
clinical data.
Collaborate with data scientists to deploy and operationalize ML
models.
6. Collaboration & Stakeholder Engagement
Align data strategy with business objectives across teams.
Engage with platform vendors (Databricks, AWS, Azure, GCP,
Informatica, Oracle, MuleSoft).
Lead PoCs, drive Databricks adoption, and provide technical
leadership.
7. Data Democratization & Self-Service Enablement
Implement self-service analytics using Databricks SQL and BI tools
(Power BI, Tableau).
Foster data literacy and enable data sharing frameworks.
Establish robust data cataloging and lineage.
8. Migration & Modernization
Lead migration from legacy platforms (Informatica, Oracle, Hadoop)
to Databricks Lakehouse.
Design cloud modernization roadmaps ensuring minimal disruption.
--
Shivam Kumar
Technical recruiter | Empower Professionals
......................................................................................................................................
ShivamK@empowerprofessionals.com |
100 Franklin Square Drive – Suite 104 | Somerset, NJ 08873
www.empowerprofessionals.com
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