Manager

ExlService Holdings, Inc.; Gurgaon, Bengaluru; On-site; INR 2,500,000 - 4,000,000; Full time

Benefits offered by this job

Exposure to Cutting-Edge Tech

Leadership Pathway

Collaborative Environment

Competitive Package

Job summary

EXL Sports Analytics seeks an AI Engineer to architect scalable data lakehouse solutions across cloud providers, moving beyond scripts to production-grade pipelines. You will design robust data products, focusing on quality and governance within a fast-growing sports analytics practice.

You will work with PySpark, Snowflake, DBT, and GenAI tools, shaping data-driven decisions while collaborating with data scientists and consultants to solve sports industry problems.

Qualifications

• Graduate in Data Science, Computer Science, Statistics, or a related field.
• 4-6 years of experience in data science or data analysis.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines using PySpark and Advanced SQL.
• Architect data ingestion on Snowflake, leveraging S3/ADLS, serverless services and modern data warehouses.
• Utilize DBT, Snowpark notebooks, Snowflake Stored procedures and tasks for data transformation and orchestration.
• Champion software engineering best practices: version control, unit tests, and API documentation.
• Utilize AI coding assistants to accelerate development cycles and improve code efficiency.
• Design and implement automated data quality checks across ingestion, transformation, and reporting layers.
• Define, monitor, and report data quality metrics and work with stakeholders to resolve issues.

Skills

PySpark

Advanced SQL

Python scripting

Snowflake

Data Modeling

CI/CD & Testing

GenAI tools

Education

Bachelor's in Data Science / CS / Statistics

Tools

Git

DBT

Airflow

Job description

Manage data science projects and ensure alignment with business goals. Ensure adherence to data science policies and procedures. Provide strategic guidance on data science practices. Lead a team of data scientists.

Responsibilities

Job Title:
AI Engineer
Location:
[Remote / On-site / Hybrid]
About the Team
Join the EXL Sports Analytics team, where passion meets precision. We provide data-driven, action-oriented solutions to some of the topmost sports organizations in the world. Our work goes beyond traditional reporting; we leverage Machine Learning, Generative AI, and advanced algorithms to solve complex business problems through a consultative approach.
We operate at the cutting edge of technology, building scalable solutions that power decisions in the sports industry. We foster a culture of curiosity and continuous learning, where we don’t just use tools—we evaluate and implement the best open-source and proprietary technologies available.
About the Role
We are looking for a curious and driven AI Engineer to join our team. In this role, you will architect and build scalable data lakehouse solutions across major cloud providers. You will move beyond simple script writing to engineer robust, production-grade pipelines using the Modern Data Stack.
You will act as both an individual contributor, ensuring high code quality and leveraging AI-assisted development tools (like Cursor, Claude, or GitHub Copilot) to maximize efficiency and innovation.

• Big Data Engineering: Design, build, and maintain scalable ETL/ELT pipelines using PySpark and Advanced SQL to process massive datasets.
• Platform Architecture: Implement data ingestion infrastructure on Snowflake, leveraging cloud storage (S3/ADLS), serverless services, and modern data warehouses.
• Transformation & Orchestration: Utilize DBT (Data Build Tool), Snowpark notebooks, Snowflake Stored procedures and tasks for effective data transformation and manage job orchestration/scheduling.
• Code Quality & Best Practices: Champion software engineering best practices, including version control (Git), writing comprehensive unit tests, and maintaining design/API documentation.
• AI-Augmented Development: Actively utilize AI coding assistants (Cursor, Copilot, etc.) to accelerate development cycles and improve code efficiency.
• Data Quality Checks: Design and implement automated data validation checks across ingestion, transformation, and reporting layers to ensure completeness, accuracy, consistency, timeliness, and uniqueness of data.
• Data Quality Measures: Define, monitor, and report on data quality metrics, thresholds, and exception handling processes; partner with stakeholders to resolve data issues and improve trust in analytics outputs.

What We Offer

• Exposure to Cutting-Edge Tech: Hands-on work with multiple cloud providers, prominent data platforms and the latest AI tools.
• Leadership Pathway: While you will contribute individually, we provide a clear pathway to grow into a leadership role where you guide the technical direction of the team.
• Collaborative Environment: A supportive work culture that values curiosity, where you will work alongside data scientists and consultants solving real-world sports business problems.
• Competitive Package: A competitive salary and benefits package designed to reward top talent.

About EXL:
EXL (NASDAQ:EXLS) is a leading data analytics and operations management company that helps businesses enhance growth and profitability in the face of relentless competition and continuous disruption. Headquartered in New York, EXL has more than 40,000 professionals in locations throughout the United States, Europe, Asia (primarily India and Philippines), Latin America, Australia and South Africa. EXL Sports Analytics team provides data-driven, action-oriented solutions to business problems through statistical data mining, cutting edge analytics techniques and a consultative approach to clients in the sports industry. We work with some of the topmost sports organizations in the world.

Qualifications

Graduate in Data Science, Computer Science, Statistics, or a related field. 4-6 years of experience in data science or data analysis.

Must-Have (Core Competencies)

• Expert PySpark Proficiency: Deep experience processing large-scale data using Spark/PySpark. You understand how distributed computing works under the hood.
• Advanced SQL: You can write complex, performant queries and understand database optimization deeply.
• Python Scripting: Strong ability to write clean, modular, and efficient Python code for data engineering pipelines.
• Platform Experience: Proven track record working within Snowflake environments.
• Data Modeling: Strong understanding of database systems, data modeling (Star schema, Snowflake schema, Medallion architecture), and data architecture.
• Engineering Mindset: Experience with CI/CD, unit testing, and integrating with existing codebases.
• AI Adaptability: Proficiency/Comfort with AI-enabled software development. You should be comfortable using IDEs with GenAI tools (Cursor, VS Code with Copilot, etc.) to iterate faster.

Good-to-Have (Preferred Qualifications)

• Experience with DLT Hub and orchestration platforms like Airflow/Prefect.
• Experience with Modern Data Stack (Fivetran, Airbyte, DBT, etc.).
• Exposure to building applications using LLMs/GenAI (OpenAI SDK, Gemini, Anthropic)