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.