Overview

We are looking for an experienced Data Architect to lead the design and delivery of scalable, secure, and highperformance data solutions. The ideal candidate will have deep expertise in Databricks, big data technologies, and cloud platforms (Azure & AWS), and will play a key role in building modern data platforms that enable advanced analytics and business insights.

Key Responsibilities

• Design and implement scalable data architectures, including data lakes, data warehouses, and realtime streaming solutions.
• Build, optimize, and manage data pipelines and Delta Lake solutions using Databricks (Spark, SQL Analytics, Workflows).
• Develop cloudnative data platforms on Azure (Synapse, Data Factory, Data Lake) and AWS (Redshift, Glue, S3).
• Create and automate ETL/ELT workflows using Apache Spark, PySpark, and cloud services.
• Design and maintain robust data models (dimensional, normalized, star schema) to support analytics and reporting.
• Work with big data technologies such as Hadoop, Kafka, and Scala for largescale data processing.
• Ensure data governance, security, and compliance with industry standards like GDPR and HIPAA.
• Optimize Spark workloads, storage, and compute resources for performance and cost efficiency.
• Collaborate closely with engineering, analytics, and business teams to align data solutions with organizational goals.

Required Skills

• 8+ years of experience in data architecture, data engineering, or analytics roles.
• Strong handson experience with Databricks (Delta Lake, Spark, MLflow, Pipelines).
• Expertise in Azure (Synapse, Data Lake, Data Factory) and AWS (Redshift, S3, Glue).
• Strong programming skills in SQL, Python, or Scala.
• Experience with NoSQL databases (e.g., MongoDB) and streaming platforms (Kafka).
• Solid understanding of data governance, security, and compliance best practices.
• Excellent problemsolving, communication, and crossteam collaboration skills.