Job Description

About US:-

We turn customer challenges into growth opportunities.

Material is a global strategy partner to the world's most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences.

We use deep human insights, design innovation and data to create experiences powered by modern technology. Our approaches speed engagement and growth for the companies we work with and transform relationships between businesses and the people they serve.

Srijan, a Material company, is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners.

Be a part of an Awesome Tribe

- Databricks Architect

Key Responsibilities:

Lead the architecture, design, and implementation of end-to-end data solutions on the

Databricks Lakehouse Platform

.

Build and optimize scalable data pipelines for structured and unstructured data using

Apache Spark

on Databricks.

Define and enforce data engineering and architectural best practices.

Collaborate with data scientists, analysts, and business stakeholders to understand requirements and translate them into scalable solutions.

Architect and lead the design of

CI/CD pipelines

and automation for Databricks Pipelines.

Ensure data governance, security, and compliance in all solutions.

Provide technical leadership and mentorship to data engineering teams.

Evaluate new tools and technologies to continuously improve platform efficiency and performance.

Work with Azure/AWS/GCP cloud environments integrated with Databricks.

Required Skills & Qualifications:

8+ years of hands-on experience with Databricks

, including Spark, Delta Lake, MLflow, and DBSQL.

Strong experience in building large-scale

ETL/ELT data pipelines

.

Solid knowledge of

data modeling

,

data warehousing

, and

distributed computing

.

Experience with

cloud platforms

(Azure, AWS, or GCP), preferably Azure.

Proven track record of implementing

best practices

in data engineering and architecture.

Proficiency in

Python

,

SQL

, and Spark-based processing.

Strong understanding of

DevOps practices

in the context of Databricks (CI/CD, infrastructure as code).

Excellent communication and stakeholder management skills.

Good to Have:

Experience or working knowledge of

Microsoft Fabric

.

Familiarity with

Power BI

,

Synapse Analytics

, or other modern BI tools.

*

Certifications related to Databricks or Azure (e.g.,

Databricks Certified Data Engineer

,

Microsoft Certified: Azure Solutions Architect

)