Data Engineer

About the Role

ConvergeSPORTS is a product-driven business combining Deloitte's sports industry experience with proprietary data, AI-native decision intelligence, and reusable Converge capabilities. As a Data Engineer based in US-India (USI), you will build the data pipelines that turn raw sports data into production-grade foundations for ConvergeSPORTS products, powering analytics, machine learning, and AI-enabled decision experiences.

Key Responsibilities

• Build Data Pipelines
• Build and maintain batch data pipelines using SQL, Python, and PySpark to ingest, transform, and serve fan, sponsorship, ticketing, CRM, and commercial datasets.
• Develop components of reusable ETL/ELT frameworks under the guidance of senior engineers, following established design patterns and coding standards.
• Write, test, and tune SQL and Python code for correctness and performance, with unit tests and clear documentation.
• Make Data Trustworthy
• Implement data quality checks, validation routines, and lineage documentation that make data assets trustworthy for product use.
• Contribute to data models and schemas that support analytics, machine learning, and agentic product features.
• Ship as One Team
• Partner with product managers and data scientists to translate defined requirements into production-ready data assets and feature pipelines.
• Support deployment, monitoring, and troubleshooting of pipelines in production, working with application engineering and DevOps teams on CI/CD and observability.
• Participate in Agile ceremonies and code reviews, and keep work items, estimates, and status current for USI and US stakeholders.
• Help standardize data adapters and schemas across the ConvergeSPORTS product portfolio by documenting and reusing existing patterns.

Requirements & Tech Stack

• Bachelor's degree in Computer Science, Engineering, Information Technology, Mathematics, Statistics, or a related field, or equivalent experience.
• 2-4 years of hands-on experience building and supporting data pipelines in product, platform, or data-intensive delivery environments.
• Proficiency in SQL and Python, including writing, testing, and tuning data transformation code.
• Experience with at least one cloud data platform such as Snowflake, Databricks, BigQuery, or PostgreSQL.
• Experience with Spark/PySpark or comparable distributed data processing frameworks, and with workflow orchestration.
• Experience with Git/GitHub, branching, code review, and Agile product development.
• Based in India, able to work virtually with US stakeholders.

Preferred Qualifications

• Experience with sports, media, entertainment, sponsorship, ticketing, CRM, loyalty, or fan engagement data.
• Experience with Delta Lake or lakehouse patterns, Airflow, Databricks Workflows, or dbt.
• Experience with Docker, CI/CD, and cloud deployment on AWS, Azure, or GCP.
• Experience preparing data for AI, recommendation, scoring, or segmentation use cases.

Core Competencies

• Curious and quick to learn, acts on feedback from senior engineers.
• Detail-oriented, treats data accuracy, testing, and documentation as part of the work.
• Clear communicator who raises blockers early across USI and US teams.
• Collaborative with product, data science, and engineering.
• Owns assigned work from start to finish, with growing independence.