Senior Data Engineer Job Sportserve

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About the role:

As a Senior Data Engineer, you will take ownership of designing, building, and maintaining scalable, high-performance data pipelines that drive analytics, reporting, and machine learning across the organization. You’ll lead initiatives to improve data architecture, ensure reliability and quality, and mentor junior engineers, enabling data-driven decisions at every level of the business.

Responsibilities

• Design, build, deploy, and maintain scalable and reliable data pipelines for batch and real-time data processing.
• Develop and maintain data ingestion, transformation, and loading (ETL/ELT) processes across multiple data sources and platforms.
• Work closely with Data Scientists, Business Analysts, and Software Engineers to support analytical, reporting, and machine learning use cases.
• Ensure data solutions meet requirements for performance, availability, scalability, and reliability.
• Contribute to the design and maintenance of data warehouses and data lakes, primarily on Google Cloud Platform (GCP), with flexibility for other cloud platforms as needed.
• Monitor data pipelines and resolve incidents, identifying root causes and implementing long-term fixes.
• Participate in the full software development lifecycle including development, testing, deployment, and operations (DevOps).
• Collaborate with stakeholders to improve data governance, data quality, and overall data architecture.
• Optimize and enhance existing ETL processes and data platforms.
• Create and maintain technical documentation for data pipelines, systems, and workflows.
• Work in an Agile environment and actively contribute to sprint planning, reviews, and retrospectives.
• Support Self-Service BI and analytics use cases by delivering well-structured and reliable datasets.
• Proactively suggest improvements to data systems, performance, and development practices.
• Keep up to date with emerging technologies in data engineering, big data, and cloud-native solutions.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
• 3–5 years of hands-on experience in Data Engineering
• Strong experience in Python for data engineering and backend development.
• Advanced knowledge of SQL and experience with relational databases (BigQuery, MySQL, Snowflake, etc.).
• Experience with graphical tools (preferably NiFi) for ETL/ELT pipeline development and optimization.
• Experience with cloud platforms, preferably GCP.
• Experience with real-time streaming platforms such as Kafka, MQTT.
• Solid understanding of data modeling, data structures, and distributed systems.
• Working knowledge of NoSQL databases (e.g., Firestore, MongoDB, or similar).
• Familiarity with CI/CD pipelines and automation tools (GitLab, SonarQube, Docker, etc.).
• Experience with API integration and development.
• Strong analytical thinking and problem-solving skills.
• Ability to work independently and as part of a team in a fast-paced environment.
• Good written and spoken English communication skills.

How to Apply

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