Senior Data Engineer, Confluent

• Successful candidates will have strong technical capabilities, leadership experience, a can-do attitude, and are highly collaborative
• 6+ years of experience in a Data Engineering role, with a focus on data warehouse technologies, data pipelines, and BI tooling
• 1-3 years of team leadership, management, or equivalent project leadership experience (formal management preferred, but will consider dotted line management or technical leadership roles)
• Bachelor or advanced degree in Computer Science, Mathematics, Statistics, Engineering, or related technical discipline
• Expert knowledge of SQL and relational & cloud database systems and concepts
• Strong knowledge of data architectures, data modelling and data infrastructure ecosystem
• Experience with enterprise business systems such as Salesforce, Marketo, Zendesk, Clari, Anaplan, etc
• Experience with ETL pipeline tools like Airflow, and DBT, and with code version control systems like Git
• Demonstrated ability to see the big picture and translate business needs into technical requirements
• Strong stakeholder management skills and ability to effectively prioritize competing demands
• The ability to communicate cross-functionally, derive requirements and architect shared datasets; the ability to synthesize, simplify, and explain complex problems to different types of audiences, including executives
• Proven track record of mentoring junior engineers and helping them grow technically
• The ability to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful

Desirable

• The mission of the Data Science/Data Engineering team at Confluent is to serve as the central nervous system of all things data for the company: we build data and analytics infrastructure, insights, models and tools, to empower data-driven thinking, and optimize every part of the business
• This position offers limitless opportunities for an ambitious data engineering leader to make an immediate and meaningful impact within a hyper-growth start-up, and contribute to a highly engaged open source community
• This is a partnership-heavy role. As a Team Lead within the Data organization, you will enable various functions of the company, i.e. Product, Engineering, Field Operations, Go-to-Market, etc., to be data-driven while providing leadership and direction to your team.
• As a Data Engineer, you will take on big data challenges in an agile way. You will participate and guide your team in building data pipelines that enable data scientists, analytics partners, operation teams, and executives to make data accessible to the entire company
• You will also build data models to deliver insightful analytics while ensuring the highest standard in data integrity. You are encouraged to think out of the box and play with the latest technologies while exploring their limits
• Lead a team of data engineers, providing technical guidance, mentorship, and career development
• Partner with stakeholders across the organization to understand business needs, prioritize features, and develop strategic data solutions
• Break down complex projects into manageable tasks and assign them to team members based on their strengths and development goals
• Design, build and launch extremely efficient and reliable data pipelines to move data across many platforms including Data Warehouse and real-time systems
• Developing strong subject matter expertise and managing the SLAs for those data pipelines
• Set up and improve BI tooling and platforms to help the team create dynamic tools and reporting
• Partnering with Data Scientists and business partners to develop internal data products to improve operational efficiencies organizationally
• Foster a culture of innovation, collaboration, and technical excellence within your team
• Represent the data engineering team in cross-functional meetings and advocate for technical best practices
• Here are some examples of our work:
• Data Pipelines - Create new pipelines or rewrite existing pipelines using SQL, Python on Airflow & DBT
• Data Quality and Anomaly Detection - Improve existing tools to detect anomalies real time and through offline metrics
• Data Modeling - Partner with analytic consumers to improve existing datasets and build new ones
• Technical Leadership - Guide the team towards maintaining a high technical bar while collaborating with stakeholders to deliver overall impact