Data Architect

Role Overview:

Data Architect - Databricks designs and implements scalable data architectures and solutions. The jobholder has expertise in Databricks Lakehouse, data modeling, and cloud integration, ensuring high performance, security, and reliability.

Key Technical Skills & Responsibilities

12+ years of experience in data engineering using Databricks or Apache Spark-based platforms.

Proven track record of building and optimizing ETL/ELT pipelines for batch and streaming data ingestion.

Hands-on experience with Azure services such as Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, or Azure SQL Data Warehouse.

Proficiency in programming languages such as Python, Scala, or SQL for data processing and transformation.

Expertise in Spark (PySpark, Spark SQL, or Scala) and Databricks notebooks for large-scale data processing.

Familiarity with Delta Lake, Delta Live Tables, and medallion architecture for data lakehouse implementations.

Build and query deltalake storage solutions

Process streaming data with Azure Databricks structured streaming

Design Azure Databricks security and data protection solutions

Flatten nested structures and explode arrays with spark

Transfer data outside using sparkpools using pyspark connector

Optimizing spark jobs

Implementing best practices in spark/databricks

Experience with orchestration tools like Azure Data Factory or Databricks Jobs for scheduling and automation.

Knowledge of Git for source control and CI/CD integration for Databricks workflows, cost optimization, performance tuning.

Familiarity with Unity Catalog, RBAC, or enterprise-level Databricks setups.

Ability to create reusable components, templates, and documentation to standardize data engineering workflows.

Solutioning and presales - Architecting frameworks, defining roadmaps, and engaging with stakeholders.

Experience in defining data strategy, evaluating new tools/technologies, and driving adoption across the organization.

Experience with Snowflake and/or Microsoft Fabric is an added advantage.

Must have experience of working with streaming data sources and Kafka (preferred).

Eligibility Criteria:

Bachelor's degree in computer science, Information Technology, or related field

Proven experience as a Databricks Architect or similar role

Complete knowledge in Databricks platform architecture

Databricks certification (e.g., Certified Data Engineer)

Expertise in Python/Scala/ SQL/R

Knowledge of MLOps, data observability, DevOps/CI-CD, and BI tools.

Experience with DataOPS & AIOPS

Experience with cloud platforms like AWS, Azure, or GCP or Alibaba

Strong understanding of data modeling and cloud integration

Experience with cluster sizing and security implementation

Excellent problem-solving and communication skills