Responsibilities:
- Design, build, and optimize data pipelines that support critical foundational, cross-cutting product services, empowering the product team to make informed decisions.
- Drive advancements in our Data Engineering stack by implementing containerization, refining data modeling techniques, and evolving ETL pipeline development to support emerging business needs and scalability requirements.
- Leverage your data modeling expertise to design, build, and maintain our analytics data warehouse that delivers reliable, high-quality datasets for reporting, analytics, and machine learning purposes, supporting both short-term insights and long-term strategic initiatives.
- Advocate for Data Engineering best practices within the team, championing their adoption and supporting the continuous improvement of the team's capabilities.
- Work with stakeholders across the organization to understand their data needs and translate these needs into actionable data solutions.
- 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 in data engineering, delivering data products from conception to delivery and supporting their underlying infrastructure.
- Strong technical background in building and optimizing data pipelines, with proficiency in Python, SQL, and data modeling for different types of data sources and business processes.
- Technical expertise in the following: Python, Go, Kubernetes, Docker, Terraform, CircleCI, GitHub Actions, Kafka, PubSub, Dataflow, Redshift, BigQuery, Databricks, dbt, Looker
- Experience with cloud environments such as GCP, AWS, or Azure
- Strong communication skills (written and verbal), with an ability to work collaboratively with cross-functional teams, including backend engineering, data science, and product teams.
- Effective analytical, troubleshooting, and problem-solving skills, ensuring data systems operate efficiently and meet business needs.
- Mentorship experience, with a focus on guiding junior data engineers and contributing to team growth through knowledge-sharing and code reviews.
- A degree in computer science, engineering, or a related field.
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