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Solutions Architect - Sports - Databricks
Solutions Architect
Lead end‑to‑end cloud data solutions for sports analytics, leveraging Databricks, Spark, and Python to architect scalable pipelines and deliver actionable insights.
About the role
Key Responsibilities
- Design and implement end‑to‑end data pipelines on Databricks, ensuring high performance and reliability for sports data ingestion and processing.
- Collaborate with data scientists and product teams to translate business requirements into scalable Spark jobs and ML workflows.
- Architect cloud solutions on AWS/GCP/Azure, optimizing cost, security, and compliance for large‑scale analytics workloads.
- Mentor and guide engineering teams on best practices for data modeling, versioning, and CI/CD in a data‑centric environment.
- Conduct performance tuning, monitoring, and troubleshooting of Spark clusters and data pipelines.
Requirements
- 5+ years of experience in cloud data architecture, with a strong focus on Databricks and Apache Spark.
- Proficiency in Python, SQL, and data engineering concepts such as ETL, data lakes, and lakehouses.
- Hands‑on experience with cloud platforms (AWS, GCP, or Azure) and related services (S3, Redshift, BigQuery, Synapse).
- Excellent communication skills and ability to translate complex technical concepts to non‑technical stakeholders.
- Experience in the sports or entertainment domain is a plus.
Skills
databricksapache sparkpythonsql