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Merkle, Inc.

Data Science & AI Engineer

INOn-siteIndividual contributorvia jobspy_indeed
pythonsqlazureetlllmapipostmandata analysis

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### **Insights \& Analysis**

DGS India \- Bengaluru \- Manyata N1 Block #### **About the job**

**Data Science \& AI Engineer** **(Azure, GenAI, Data \& Decisioning Systems)** ===============================================================================

**Role Summary**

We are seeking a motivated and hands\-on Data Science \& AI Engineer (L35\) to support the development and implementation of data\-driven and AI\-powered solutions. This role works under the guidance of the Lead Full Stack Engineer (L40\) and focuses on execution, experimentation, and delivery of data pipelines, analytics, and AI\-enabled features.

The ideal candidate will contribute to building, testing, and integrating data and AI components, while gaining exposure to enterprise systems and evolving toward broader technical responsibilities over time.

**Core Responsibilities**

**Data Engineering \& Processing**

* Develop and maintain data pipelines for ingesting data from APIs, databases, and flat files * Implement ETL/ELT processes using Python and SQL * Perform data cleaning, transformation, and validation * Support integration of data across internal and external systems * Assist in maintaining data workflows and troubleshooting data issues

**Data Analysis \& Reporting**

* Support development of reports, dashboards, and analytical datasets * Perform exploratory data analysis to generate insights * Prepare datasets for analytics and AI use cases * Collaborate with stakeholders to understand reporting and data needs

**AI / ML Implementation**

* Support development of AI\-powered application features * Integrate with pre\-built LLM APIs and AI services * Assist in prompt design and experimentation * Contribute to basic retrieval and knowledge\-based systems * Test and evaluate AI outputs for accuracy and performance

**Application \& API Support**

* Assist in integrating data and AI components into APIs and backend systems * Support API testing, validation, and debugging (e.g., Postman) * Collaborate with frontend and backend teams to enable data\-driven features

**Database Development**

* Write and optimize SQL queries for data extraction and transformation * Support database schema updates and maintenance * Ensure data consistency and basic performance optimization

**Cloud \& Platform Support (Azure)**

* Assist in deploying and managing data and AI workloads on Azure * Support configuration of cloud resources under guidance * Monitor system performance and assist in troubleshooting issues

**Security \& Compliance Support**

* Follow secure coding practices for data and AI solutions * Assist in implementing authentication and access controls * Ensure adherence to data governance and compliance standards

**Internal Tools \& Platform Support (Retool)**

* Assist in building and maintaining Retool applications * Support development of internal tools and dashboards * Integrate applications with APIs and data sources

**Collaboration \& Development**

* Work closely with the Lead Full Stack Engineer (L40\) on execution and delivery * Collaborate with cross\-functional teams across engineering, data, and product * Participate in code reviews, design discussions, and knowledge\-sharing * Continuously learn and adopt best practices in AI, data engineering, and software development

**Profile Summary**

* Strong foundation in Python and SQL for data processing * Basic understanding of APIs, backend systems, and application integration * Familiarity with AI/ML concepts and LLM\-based tools * Exposure to cloud platforms (Azure preferred) * Strong analytical thinking and problem\-solving ability * Ability to work effectively in a guided, team\-oriented environment

**Preferred / Good to Have**

* Experience with vector databases (e.g., Azure AI Search or similar) * Exposure to cloud\-native backend systems and APIs * Basic understanding of MLOps, CI/CD, and model lifecycle management * Knowledge of data engineering concepts (CDC, incremental loads, streaming pipelines) * Familiarity with monitoring, observability, and performance tuning * Understanding of Responsible AI practices and governance * Experience with analytics tools (e.g., Power BI, Tableau)

**Preferred Media Domain Experience**

* Programmatic advertising systems (DSP, SSP) * Personalization and recommendation platforms * Identity resolution and post\-cookie ecosystem * Marketing analytics, attribution, and campaign optimization systems * Ad\-tech ecosystem – programmatic advertising (DSP/SSP), targeting, identity resolution, and campaign performance measurement

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