Databricks Architect

Marlabs; Bengaluru; On-site; INR 4,200,000 - 7,000,000; Full time

Job summary

Marlabs is seeking a Databricks Architect in Bengaluru to design and govern scalable data platforms that support enterprise reporting and advanced analytics. You will lead end‑to‑end Databricks implementations, mentor engineers, and align data initiatives with business objectives.

The role requires hands‑on Databricks experience, strong Spark and Delta Lake skills, and proven ability to drive architecture decisions across cloud platforms.

Qualifications

• 10+ years of experience in data engineering or analytics platforms.
• Hands-on Databricks design and implementation expertise.
• Strong Spark, SQL, and Delta Lake skills for large-scale processing.
• Experience with cloud platforms (AWS/Azure/GCP) and data governance.

Responsibilities

• Design end-to-end data platforms using Databricks Lakehouse architecture.
• Define and implement scalable batch and streaming data pipelines.
• Translate functional requirements into technical designs with cross-functional teams.
• Establish data modeling, performance optimization, and cost‑management best practices within Databricks.
• Lead cloud-based implementations across AWS, Azure, or GCP, including security and access controls.
• Provide architecture reviews, code reviews, and design sessions.
• Troubleshoot data quality, performance, and reliability in production environments.

Skills

Databricks

Apache Spark

SQL

Delta Lake

Cloud platforms

Data governance

CI/CD & IaC

Mentoring

Data modeling

Batch & streaming

Architecture leadership

Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Databricks Architect to join our innovative and dynamic team.

Databricks Architect | About You

As a Databricks Architect, you are responsible for designing, implementing, and governing scalable data and analytics platforms that support enterprise reporting, advanced analytics, and data‑driven decision making. You play a hands‑on role in shaping data architecture, setting technical standards, and ensuring Databricks solutions are built for performance, reliability, and long‑term scalability. You work closely with data engineers, analysts, and business stakeholders to guide solution design, review implementations, and ensure alignment with business objectives. You are actively involved in platform optimization, cost management, and the adoption of best practices across data ingestion, transformation, and analytics. As a technical leader, you mentor team members, influence architectural decisions, and help mature the organization’s overall data capabilities.

Databricks Architect | Day-to-Day

• Design and architect end‑to‑end data platforms using the Databricks Lakehouse architecture.
• Define and implement scalable batch and streaming data pipelines using Apache Spark and Delta Lake.
• Partner with engineering, analytics, and business teams to translate functional requirements into technical designs.
• Establish and enforce data modeling, performance optimization, and cost‑management best practices within Databricks.
• Lead cloud‑based implementations across AWS, Azure, or GCP, including networking, security, and access controls.
• Provide technical leadership through architecture reviews, code reviews, and design sessions.
• Support production environments by troubleshooting data quality, performance, and reliability issues.

Databricks Architect | Skills & Experience

• 10+ years of overall experience in data engineering, data architecture, or enterprise analytics platforms.
• Hands‑on experience designing and implementing solutions on Databricks.
• Strong proficiency in Apache Spark, SQL, and Delta Lake for large‑scale data processing.
• Experience building and optimizing both batch and real‑time data pipelines.
• Proven experience working within at least one major cloud platform, including AWS, Azure, or GCP.
• Solid understanding of data governance concepts including security, lineage, access control, and compliance.
• Experience with data modeling techniques for analytical and reporting workloads.
• Familiarity with CI/CD practices, version control, and infrastructure‑as‑code approaches for data platforms.
• Demonstrated ability to mentor engineers and lead technical design discussions in cross‑functional teams.