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Databricks Architect

Nityo Infotech CorporationIrvine, CA🇺🇸United States

Why this role stands out

As a Databricks Architect, you'll design and implement cutting-edge data solutions on AWS, driving impactful analytics and ML initiatives across the enterprise. This hybrid role is perfect for experienced architects who thrive on building scalable, reliable data platforms and collaborating with diverse teams to shape data strategy. Embrace this opportunity to grow your expertise within a reputable organization.

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationIrvine, CA, United States
Stakeholder ManagementSQLGitApache SparkAWSMLOpsMLflowDatabricksTerraformRESTMachine LearningCI/CDDelta LakeIAM

Job description

The Databricks Architect is responsible for designing, implementing, and optimizing scalable data engineering and analytics solutions on the Databricks Lakehouse Platform on AWS. This role requires deep expertise in distributed data processing, Delta Lake–based architectures, and modern data engineering best practices. The architect will partner with cross‑functional teams to define data strategies, ensure platform reliability, and enable advanced analytics, ML, and BI workloads across the enterprise.

Must Demonstrate (Critical Architectural Capabilities)

· Designing Databricks-based Lakehouse architectures on AWS

· Clear separation of compute layer vs. serving layer

· Low-latency API/data delivery strategy (cannot rely solely on Spark)

· Caching strategies for performance acceleration and cost efficiency

· Data partitioning and optimization strategy, including file-size tuning

· Ability to handle multi-terabyte structured time-series datasets

· Skill in distilling architectural significance from complex requirements

· Strong curiosity and requirement‑probing mindset

· Player‑coach leadership style (hands-on engineering + design guidance)

Required Skills & Experience

Technical Skills

· 7+ years in data engineering or data architecture.

· 3+ years hands-on with Databricks.

· Strong expertise in Spark, PySpark, SQL, and distributed data systems.

· Deep understanding of Delta Lake features (ACID, OPTIMIZE, ZORDER, Auto Loader).

· Experience with workflows/orchestration and Databricks REST APIs.

· Hands-on expertise with AWS, specifically:

o S3

o Glue / Glue Catalog

o IAM

o Lambda

o Kinesis

· Familiarity with CI/CD, Git, DevOps, and IaC (Terraform preferred).

Soft Skills

· Strong analytical and problem‑solving abilities.

· Excellent communication and stakeholder management.

· Ability to lead design discussions and guide engineering teams.

· Strong documentation and architectural blueprinting abilities.

Preferred Qualifications

· Databricks Certifications such as:

o Databricks Certified Data Engineer Professional

o Databricks Certified Machine Learning Professional

o Databricks Lakehouse Fundamentals

· Experience with MLflow, Feature Store, or MLOps pipelines.

· Experience in regulated industries (BFSI, healthcare, etc.)

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