AI Engineer 4A

Overview

Build and support data engineering solutions for reporting, analytics, Generative AI, and Agentic AI applications within the Advanced AI Practice. This hands-on individual contributor role focuses on reliable data pipelines, cloud-based data platforms, data quality, operational stability, and delivery efficiency.

What you'll do

• Develop and maintain ETL/ELT pipelines to ingest, transform, and process data from multiple enterprise systems.
• Build and support data solutions using Databricks and cloud-based platforms, including data transformations, curated datasets, and reporting data layers.
• Work with Databricks, Azure, AWS, and modern data platforms to support analytics and AI use cases.
• Perform data validation, reconciliation, and quality checks to ensure accuracy and consistency of data across systems.
• Support data migration, modernization, and platform enhancement initiatives through testing, validation, and issue resolution.
• Monitor data pipelines, investigate failures, troubleshoot issues, and support production data environments.
• Work with business analysts, data engineers, and application teams to understand requirements, clarify data needs, and deliver fit-for-purpose data solutions.
• Maintain technical documentation and contribute to data engineering standards and best practices.

What you'll need

• 2+ years of hands-on experience in data engineering or data platform development.
• Experience developing and supporting data pipelines, ETL/ELT processes, data transformations, and data integration workflows.
• Hands-on experience working with Databricks for data processing, transformation, and analytics workloads.
• Proficiency in Python and SQL for data processing, automation, and reporting requirements.
• Exposure to Azure and/or AWS cloud services and data engineering solutions.
• Experience performing data validation, troubleshooting data issues, and supporting production data pipelines.
• Familiarity with Git, CI/CD concepts, testing, and deployment practices.
• Understanding of data modeling, database concepts, reporting, and performance optimization techniques.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Proficient English language skills at C2 level.

Nice to have

• Exposure to ADF, Informatica, Talend, SSIS, or similar ETL tools.
• Experience with Power BI, Tableau, dashboard development, and business reporting.
• Familiarity with Snowflake, Azure Synapse, or other cloud data platforms.
• Knowledge of Spark, PySpark, Delta Lake, and large-scale data processing.
• Understanding of dimensional modeling, star/snowflake schemas, and data warehousing concepts.
• Exposure to Airflow, Databricks Workflows, Datadog, Azure Monitor, or similar tools.
• Familiarity with Azure, AWS, or GCP data services.
• Exposure to vector databases such as Pinecone, FAISS, Weaviate, or Milvus.
• Databricks Associate, Azure Data Fundamentals/Data Engineer, SnowPro Core, or equivalent cloud and data engineering certifications.

Details

• Location: Bangalore.
• Work mode: Hybrid.
• Employment type: Regular.
• Work shift: Day Job (India).