Data Lakehouse Architect

Role: Data Lakehouse Architect

Job Level: > 10 years of relevant experience (L4)

Duration: 12 Months

Description

We are seeking a seasoned Data Lakehouse Architect to lead the design and implementation of our data architecture leveraging technologies such as Databricks, Snowflake, and other cloud platforms. The ideal candidate will have a robust background in data engineering and architecture, ensuring that our data solutions are scalable, efficient, and secure.

Responsibilities

• You will be responsible for the end-to-end architecture of the lakehouse platform.
• This includes the design and implementation of data products, data marketplace, knowledge layer and enabling agentic workloads to run out of the lakehouse platform.
• You will also be responsible for quality assurance of the team's delivery in conformance with the Bank-defined software delivery methodology and tools.
• You will partner with other technology functions to help deliver required technology solutions.

• Other responsibilities include:
• Provide technical vision and create roadmaps for the lakehouse platform
• Create the target architecture for an application / set of applications with emphasis on platforms, reusability, scalability and security
• Create frameworks, technical features which helps in faster operationalisation of new patterns such as unstructured content extraction, lambda architecture deployment patterns, retrieval-augmented data patterns, agentic workloads etc
• Effectively partner with business users to design data contracts, SLA, data quality rules for data products
• Independently install, customise and integrate software packages and programs
• Participate in selection of product/tools via RFP/POC.
• Create technical documents (functional/non-functional specification, design specification, training manual) for the solutions. Review design specifications created by development team
• Performance engineering and tuning
• Execute continuous service improvement and process improvement plans

Skills and Qualifications

• 10-12 years of experience in data architecture and engineering with a focus on data lakehouses.
• Strong expertise in Databricks, Snowflake, Cloudera, and cloud platforms such as AWS, Azure, Google Cloud.
• Proficient in SQL and programming languages such as Python or Scala.
• Experience with data modeling, ETL processes, and data warehousing solutions.
• Familiarity with big data technologies (e.g., Spark, Hadoop) and data orchestration tools (e.g., Airflow, Apache NiFi).
• Understanding of data governance, security, and compliance frameworks.
• Excellent communication skills and ability to work collaboratively in a team environment.