Senior Data Engineer- Remote, India

This is a remote position.

Job Description

We are seeking a Technical Architect with 10+ years of overall technology experience, including proven experience architecting and delivering production Generative AI systems. The ideal candidate will combine deep hands-on command of large language models, retrieval-augmented generation, and agentic architectures with the judgement to design AI solutions that hold up under real enterprise constraints of cost, latency, security, and compliance. This role owns the technical architecture of AI engagements end-to-end: shaping the solution during discovery and pre-sales, defining reference architectures and integration patterns, selecting models and platforms, and guiding delivery teams through implementation. You will work directly with client stakeholders, product managers and engineering leads, and will help set the technical standards of our AI practice. This is a senior, hands-on architecture role rather than a purely advisory one. This role owns multiple concurrent AI engagements from discovery through production. Beyond technical architecture, the Technical Architect is expected to act as a trusted advisor to clients, lead engineering teams, mentor future technical leaders, and drive engineering excellence through hands-on involvement

Requirements

Job Description

We are looking for a well-rounded Senior Data Engineer to proactively design, build and maintain modern cloud data platforms end to end. The role spans the full data engineering lifecycle - ingestion, transformation, storage, modeling and delivery - with strong hands-on expertise across Azure, Databricks and Snowflake, fully automated CI/CD, and integration of enterprise source systems including SAP. It requires cross-functional collaboration and ensures the highest standards of data quality, reliability and performance.

Responsibilities

• Understand the values and vision of the organization

• Protect the Intellectual Property

• Adhere to all the policies and procedures

• Design, develop, and maintain scalable data pipelines for data ingestion, processing and storage.

• Build and optimize data architectures and data models (Lakehouse / medallion, dimensional) for efficient data storage and retrieval.

• Develop ETL/ELT processes to transform and load data from various sources into data warehouses and data lakes.

• Build and orchestrate pipelines on Azure Databricks using PySpark, Spark SQL and Delta Lake, orchestrated with Databricks Workflows.

• Integrate data from enterprise source systems including SAP (ABAP/CDS extracts, RPA/CSV or connectors) and load into Snowflake and Databricks.

• Own end-to-end CI/CD for data pipelines using Databricks Asset Bundles (DAB) and Azure DevOps (Git repositories, YAML build and release pipelines), promoting code across dev, QA and production.