Senior Data Engineer - AI and Data Science Engineer III

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. We help sports organizations grow revenue, deepen fan engagement, optimize partnerships, and improve commercial performance while operating with the focus of a product company. Sports organizations generate enormous volumes of fan, ticketing, sponsorship, and commercial data, but it only creates value when it is trusted, connected, and ready to use. As a Senior Data Engineer based in US-India (USI), you will design and 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, while mentoring and guiding the engineers around you. If you are an experienced engineer who wants to own real product infrastructure for the sports industry and grow into technical leadership, this is where you will do it. Key Responsibilities Build Data Pipelines Design, build, and maintain batch data pipelines using SQL, Python, and PySpark to ingest, transform, and serve fan, sponsorship, ticketing, CRM, and commercial datasets Design and develop reusable ETL/ELT frameworks, define design patterns and coding standards, and guide Consultant-level engineers in applying them Write, test, and tune SQL and Python code for correctness and performance, with unit tests and clear documentation, and raise the quality bar through thorough code reviews Make Data Trustworthy Define and implement data quality checks, validation routines, and lineage documentation that make data assets trustworthy for product use Design data models and schemas that support analytics, machine learning, and agentic product features, and review models and schemas developed by others Ship as One Team Partner with product managers and data scientists to shape requirements, clarify ambiguous problems, and translate them into production-ready data assets and feature pipelines Own deployment, monitoring, and troubleshooting of pipelines in production, working with application engineering and DevOps teams on CI/CD and observability, and lead resolution of production issues Drive Agile ceremonies and code reviews for your workstream, and keep work items, estimates, and status current while communicating risks and tradeoffs to USI and US stakeholders Help standardize data adapters and schemas across the ConvergeSPORTS product portfolio by defining, documenting, and evolving reusable patterns Lead and Develop Others Mentor and coach Consultant-level engineers through pairing, onboarding, and code review to build their technical skills and independence Break down work, estimate, and coordinate delivery for a small group of engineers, and escalate risks early Contribute to technical direction by recommending tools, architecture, and engineering practices, and by influencing design decisions across the ConvergeSPORTS product portfolio Represent engineering in conversations with US-based product and engineering leaders, and communicate technical tradeoffs clearly to non-technical stakeholders Reporting Relationships Reports to Li-Shen Lee. Provides day-to-day technical guidance to Consultant -level data engineers. Works as one team with product management, data science, and application engineering, partners with US-based ConvergeSPORTS product and engineering leaders, and collaborates with DevOps and delivery teams across USI. Qualifications Required Bachelor's degree in Computer Science , Engineering, Information Technology, Mathematics, Statistics, or a related field, or equivalent experience 5-7 years of hands-on experience designing, building, and supporting data pipelines in product, platform, or data-intensive delivery environments, including end-to-end ownership of production pipelines 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 Demonstrated experience leading a workstream or small team, mentoring junior engineers, and leading code reviews Ability to translate ambiguous business needs into technical designs and to communicate tradeoffs to technical and non-technical stakeholders Based in India, able to work virtually with US stakeholders Preferred 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 continuously learning, brings new tools and practices to the team and seeks feedback to keep growing Detail-oriented, treats data accuracy, testing, and documentation as part of the work and holds the team to the same standard Clear communicator who raises risks and blockers early and engages confidently with senior stakeholders across USI and US teams Collaborative with product, data science, and engineering, and builds trust across teams Owns outcomes for a workstream from start to finish, with high independence and accountability for the team's output Leads by example: mentors others, sets a high bar for quality, and builds team capability Why This Role Matters Every ConvergeSPORTS product decision, from fan engagement to sponsorship optimization, depends on data that teams can trust. As a Senior Data Engineer, you will build the pipelines behind that trust, set the standard for how they are built, and help grow the engineers around you on products used across the sports industry.