Senior Data Software Engineer, Tinder

• We're looking for someone who is passionate about answering timely business questions through data and empowering colleagues to fully engage with data
• 5+ years of industry experience with a strong track record in data engineering and software development
• Significant knowledge of data warehousing and data modeling techniques
• Expertise in large-scale distributed data processing platforms, such as Databricks or Apache Spark
• Advanced proficiency in SQL for complex querying, data manipulation, and performance optimization
• Strong coding skills in Python, preferably in Python 3.x for data analysis and backend services
• Experience in designing, building, and maintaining ETL pipelines that ensure data quality and accessibility
• Familiarity with orchestration tools like Apache Airflow or Dagster for workflow management and automation

Desirable

• As a Senior Software Engineer, Data on the Analytics Engineering team, you will have the opportunity to build critical analytics infrastructure used to derive insights and serve several teams in the organization
• Analytics Engineering is a team within the larger Data Engineering org that works closely with Finance, Analytics, Product, Marketing, and other engineering teams to make data as easily consumable as possible
• Improve Trust in Our Data by Championing for Data Quality Across the Organization
• Take the initiative to identify and address data inconsistencies and quality issues
• Develop and implement comprehensive data validation rules and quality metrics
• Lead cross-departmental meetings to discuss data integrity and promote best practices for data management
• Create a feedback loop with stakeholders to continually enhance data standards and processes
• Influence and Help Build the Next Generation Analytics Platform at Tinder
• Contribute to the design and architecture of a scalable, efficient analytics platform that supports advanced data processing and machine learning models
• Engage in code reviews and architectural discussions to ensure high standards of code quality and design
• Stay abreast of industry trends and emerging technologies that could enhance the platform's capabilities
• Improve the Resiliency and Performance of Our Existing Platform
• Conduct performance benchmarks and optimize SQL queries and data processing scripts
• Implement robust error handling and recovery processes to enhance system uptime and reliability
• Collaborate with infrastructure teams to ensure the platform can handle increased loads and data volume
• Empower Colleagues by Building and Supporting Self-Serve Tools for Data Exploration and Analysis
• Develop intuitive, user-friendly tools that enable non-technical stakeholders to access and analyze data independently
• Conduct training sessions and create documentation to help users leverage these tools effectively
• Gather user feedback to continuously improve the functionality and user experience of these tools
• Collaborate and Build Strong Partnerships with Product, AI/ML, Data Science, Marketing and Finance
• Serve as the data liaison, ensuring clear communication and alignment on data needs and insights across various teams
• Participate in strategy sessions to help guide data-driven decision-making and prioritize data initiatives based on organizational goals
• Work closely with AI/ML and Data Science teams to define data requirements for predictive modeling and machine learning projects
• Mentor Junior Members of the Team
• Act as a role model and provide guidance on both technical skills and professional development to junior engineers and analysts
• Facilitate knowledge-sharing sessions and encourage a culture of learning and open dialogue within the team
• Assist in the onboarding process for new team members, ensuring they are well-equipped to contribute to the team’s goals effectively