Why this role stands out
Elevate your career at Hinge, where you will build the foundational data architecture that empowers millions to find meaningful connections while enjoying a highly competitive salary of up to $223,000. This role is perfect for a talented engineer who thrives in a collaborative, mission-driven environment and values the flexibility of a hybrid work schedule. Seize this incredible opportunity to shape the future of data engineering and apply today to make a lasting impact.
Quick overview
Job description
Responsibilities:
- Work with our data teams to ensure data is flowing accurately through data creation to our presentation layers.
- Improve our Data Engineering stack through containerization, data modeling, developing our ETL pipelines, and more.
- Use your expertise in data modeling to design, build, and maintain our analytics data warehouse, which provides clean, accurate, and robust data sets that can be leveraged for reporting, analytics, and machine learning initiatives.
- Work with stakeholders and translate their needs and expectations into action items and deliverables.
- Continue to learn more about the Data Engineering discipline, utilize that knowledge in your deliverables, and identify opportunities to enhance our pipelines.
- Participate in our on-call rotation to ensure system reliability, promptly addressing issues to ensure smooth operations.
What We're Looking For:
- 5+ years of professional/industry experience
- Proficient in Python, SQL, DevOps, and databases.
- 5+ years of professional/industry experience.
- Experience delivering data products from conception to delivery and with the infrastructure that supports their underlying processes.
- Experience modeling data sets for different types of sources and business processes.
- Passionate about designing elegant data infrastructure, tooling, and pipelines.
- Familiarity with our stack: Kubernetes, Docker, Terraform, Kafka, Airflow, dbt, Looker, AWS technologies (S3, Redshift), GCP technologies (Dataflow, BigQuery). and CI/CD technologies (CircleCI), Spark, Databricks
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