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Match Group

Global dating platforms with subscription model

Senior Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA$186k - $223k /yrHybrid

About the Job

Requirements

  • At least 5 years of professional or industry experience.
  • Proficiency in Python, SQL, DevOps, and databases.
  • Experience delivering data products from conception to delivery and with the infrastructure supporting their underlying processes.
  • Experience modeling data sets for different types of sources and business processes.
  • Familiarity with Kubernetes, Docker, Terraform, Kafka, Airflow, dbt, Looker, AWS technologies including S3 and Redshift, GCP technologies including Dataflow and BigQuery, CI/CD technologies including CircleCI, Spark, and Databricks.

Responsibilities

  • Work with data teams to ensure data flows accurately from data creation through presentation layers.
  • Improve the Data Engineering stack through containerization, data modeling, and developing ETL pipelines.
  • Design, build, and maintain the analytics data warehouse, providing clean, accurate, and robust data sets for reporting, analytics, and machine learning initiatives.
  • Work with stakeholders and translate their needs and expectations into action items and deliverables.
  • Continue learning about the Data Engineering discipline, apply that knowledge in deliverables, and identify opportunities to enhance pipelines.
  • Participate in the on-call rotation and promptly address issues to ensure system reliability and smooth operations.

About the Company

Match Group

Global dating platforms with subscription model

Match Group runs a family of online dating and social-discovery services. It operates a B2C model built on freemium access, with premium subscriptions and in-app purchases that unlock features like better visibility, advanced search filters, and unlimited interactions, plus an advertising channel. Its apps use a swipe-style interface and real-time, location-based discovery, supported by proprietary matchmaking algorithms and a closed-loop data ecosystem to improve experiences across brands. It emphasizes safety tools such as Face Check. The company differentiates itself by owning a large portfolio of brands (including Tinder, Hinge, and Match) and leveraging cross-brand data and technology to optimize experiences, expand into new markets, and acquire emerging platforms. Its goal is to help people form romantic relationships, friendships, and social connections at a global scale while generating recurring revenue through subscriptions and ads.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Dallas, TX
Founded
1986

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