Role Overview :

We are seeking a highly experienced Databricks Architect to lead the design, implementation, and optimization of enterprise-scale data solutions.

This role requires expertise in cloud-based data engineering, advanced analytics, and scalable architecture design.

The successful candidate will play a pivotal role in enabling data-driven decision-making across the organization.

Key Responsibilities :

- Architect and implement scalable data solutions leveraging Databricks, Apache Spark, and Delta Lake.

- Collaborate with cross-functional teams to define data strategies, pipelines, and integration frameworks.

- Optimize ETL workflows, data lakes, and machine learning environments for performance and reliability.

- Establish and enforce best practices for data governance, security, and compliance.

- Lead migration initiatives from legacy data systems to Databricks and cloud-native platforms.

- Provide technical leadership, mentoring, and architectural guidance to engineering teams.

- Stay current with emerging technologies in big data, AI/ML, and cloud ecosystems.

- Expertise with Databricks Administration performance tuning, optimization, configuration, setup, etc.

- Ability to communicate with stakeholders from Infra, legal & Info Sec.

Qualifications:

- Bachelors or Masters degree in Computer Science, Data Engineering, or related field.

- Proven experience with Databricks, Apache Spark, and cloud platforms (Azure, AWS, or GCP).

- Strong knowledge of data warehousing, ETL, and real-time streaming solutions.

- Hands-on experience with Delta Lake, MLflow, and advanced analytics frameworks.

- Excellent problem-solving, communication, and leadership skills.

Preferred Skills:

- Experience with CI/CD pipelines and DevOps practices for data engineering.

- Knowledge of containerization (Docker, Kubernetes) and microservices architecture.

- Familiarity with BI tools (Power BI, Tableau) for data visualization.