EXL

Databricks architect

EXL  •  Republic of India (Onsite)  •  12 hours ago
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Job Description

Key Role & Responsibilities

  • Define lakehouse architecture: medallion (bronze/silver/gold) patterns, batch/streaming designs, and multi-workspace strategies.
  • Design and implement data pipelines using Spark, Delta Lake, and Databricks workflows (Jobs/Workflows, DLT where applicable).
  • Establish governance and security using Unity Catalog, access controls, lineage, and data quality gates.
  • Optimise performance: cluster policies, autoscaling, partitioning, file sizing, caching, Spark tuning, and job orchestration.
  • Build CI/CD and release governance for notebooks, repos, jobs, and infrastructure-as-code.
  • Integrate Databricks with enterprise ecosystem (cloud storage, event streaming, data warehouse, BI tools).
  • Conduct solution workshops with customers; provide options and trade-offs; create phased implementation roadmaps aligned to business value.
  • Mentor teams, enforce engineering standards, and ensure operational excellence (monitoring, incident response, SRE practices).

Must Have

  • 10+ years experience with a strong Data Engineering background (ETL/ELT, distributed compute, production-grade pipelines).
  • 4+ years hands-on Databricks experience in architecture/technical leadership roles.
  • Strong experience in Apache Spark (PySpark/Scala), Delta Lake, pipeline design, and performance tuning.
  • Experience with data orchestration and DevOps practices (Git, CI/CD, testing frameworks).
  • Experience designing secure data platforms (RBAC, secrets, network/security integration, compliance considerations).
  • Strong customer-facing skills: requirements discovery, solution design, and stakeholder management.

Good to Have

  • Streaming experience (Kafka/Event Hubs, Structured Streaming, CDC patterns).
  • ML/AI enablement experience (MLflow, feature engineering, model lifecycle) as it relates to platform design.
  • Cloud certifications or platform-specific certifications.

Education

  • Bachelor’s/Master’s in Computer Science, Engineering, or related fields.

Key Skills: Databricks, Python, Spark, Data Architecture, Data Pipelines

Key Role & Responsibilities

  • Define lakehouse architecture: medallion (bronze/silver/gold) patterns, batch/streaming designs, and multi-workspace strategies.
  • Design and implement data pipelines using Spark, Delta Lake, and Databricks workflows (Jobs/Workflows, DLT where applicable).
  • Establish governance and security using Unity Catalog, access controls, lineage, and data quality gates.
  • Optimise performance: cluster policies, autoscaling, partitioning, file sizing, caching, Spark tuning, and job orchestration.
  • Build CI/CD and release governance for notebooks, repos, jobs, and infrastructure-as-code.
  • Integrate Databricks with enterprise ecosystem (cloud storage, event streaming, data warehouse, BI tools).
  • Conduct solution workshops with customers; provide options and trade-offs; create phased implementation roadmaps aligned to business value.
  • Mentor teams, enforce engineering standards, and ensure operational excellence (monitoring, incident response, SRE practices).

Must Have

  • 10+ years experience with a strong Data Engineering background (ETL/ELT, distributed compute, production-grade pipelines).
  • 4+ years hands-on Databricks experience in architecture/technical leadership roles.
  • Strong experience in Apache Spark (PySpark/Scala), Delta Lake, pipeline design, and performance tuning.
  • Experience with data orchestration and DevOps practices (Git, CI/CD, testing frameworks).
  • Experience designing secure data platforms (RBAC, secrets, network/security integration, compliance considerations).
  • Strong customer-facing skills: requirements discovery, solution design, and stakeholder management.

Good to Have

  • Streaming experience (Kafka/Event Hubs, Structured Streaming, CDC patterns).
  • ML/AI enablement experience (MLflow, feature engineering, model lifecycle) as it relates to platform design.
  • Cloud certifications or platform-specific certifications.

Education

  • Bachelor’s/Master’s in Computer Science, Engineering, or related fields.

Key Skills: Databricks, Python, Spark, Data Architecture, Data Pipelines

Key Role & Responsibilities

  • Define lakehouse architecture: medallion (bronze/silver/gold) patterns, batch/streaming designs, and multi-workspace strategies.
  • Design and implement data pipelines using Spark, Delta Lake, and Databricks workflows (Jobs/Workflows, DLT where applicable).
  • Establish governance and security using Unity Catalog, access controls, lineage, and data quality gates.
  • Optimise performance: cluster policies, autoscaling, partitioning, file sizing, caching, Spark tuning, and job orchestration.
  • Build CI/CD and release governance for notebooks, repos, jobs, and infrastructure-as-code.
  • Integrate Databricks with enterprise ecosystem (cloud storage, event streaming, data warehouse, BI tools).
  • Conduct solution workshops with customers; provide options and trade-offs; create phased implementation roadmaps aligned to business value.
  • Mentor teams, enforce engineering standards, and ensure operational excellence (monitoring, incident response, SRE practices).

Must Have

  • 10+ years experience with a strong Data Engineering background (ETL/ELT, distributed compute, production-grade pipelines).
  • 4+ years hands-on Databricks experience in architecture/technical leadership roles.
  • Strong experience in Apache Spark (PySpark/Scala), Delta Lake, pipeline design, and performance tuning.
  • Experience with data orchestration and DevOps practices (Git, CI/CD, testing frameworks).
  • Experience designing secure data platforms (RBAC, secrets, network/security integration, compliance considerations).
  • Strong customer-facing skills: requirements discovery, solution design, and stakeholder management.

Good to Have

  • Streaming experience (Kafka/Event Hubs, Structured Streaming, CDC patterns).
  • ML/AI enablement experience (MLflow, feature engineering, model lifecycle) as it relates to platform design.
  • Cloud certifications or platform-specific certifications.

Education

  • Bachelor’s/Master’s in Computer Science, Engineering, or related fields.

Key Skills: Databricks, Python, Spark, Data Architecture, Data Pipelines


EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com
EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.
EXL

About EXL

Choosing a digital partner is about more than capabilities — it’s about collaboration and character.

Unrealistic overhauls and off-the-shelf products ignore what matters most — your unique needs, culture, goals, and your legacy data and technology environments.

At EXL, our collaboration is built on ongoing listening and learning to adapt our methodologies. We’re your business evolution partner—tailoring solutions that make the most of data to make better business decisions and drive more intelligence into your increasingly digital operations.

Whether your goals are scaling the use of AI and digital, redesign operating models, or driving better and faster decisions, we’re here to partner with you to help you gain—and maintain—competitive advantage with efficient, sustainable models at scale.

Our expertise in transformation, data science, and change management helps make your business more efficient and effective, improve customer relationships and enhance revenue growth. Instead of focusing on multi-year, resource- and time-intensive platform designs or migrations, we look deeper at your entire value chain to integrate strategies with impact.

We use our specialization in analytics, digital interventions, and operations management—alongside deep industry expertise — to deliver solutions that help you outperform the competition.

At EXL, it’s all about outcomes—your outcomes—and delivering success on your terms. Share your goals with us and together, we’ll optimize how you leverage data to drive your business forward.

For more information, visit www.exlservice.com.

Industry
Consulting & Advisory
Company Size
10,000+ employees
Headquarters
New York, NY
Year Founded
Unknown
Website
exlservice.com
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