Staff Data Engineer

We’re looking for a Lead Data Engineer to design, build, and optimize data pipelines that power our next-generation AI-driven accounting agents. You’ll lead the development of scalable, high-performance data infrastructure while collaborating closely across teams.

Responsibilities:

• Lead data pipeline development: Build and maintain PySpark ETL pipelines with high data quality and performance
• Manage integrations: Establish robust connections to client data sources via APIs and tools like FiveTran, Plaid, and BlackLine’s own internal connector ecosystem
• Ensure reliability: Monitor pipeline performance, automate testing, and validate data accuracy
• Optimize for scale: Implement performance improvements (e.g., CDC mechanisms, indexing strategies) for large-scale datasets
• Collaborate & innovate: Work with business stakeholders to refine data requirements and integrate cutting-edge AI and big data technologies

• Design and build infrastructure for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources, including data identification, mapping, aggregation, conditioning, cleansing, and analyzing.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements and deliver valuable insights.
• Effectively communicate complex technical concepts to non-technical audiences.
• Desire to automate everything.
• Maintain documentation and operational knowledge base.
• Coach and technically train junior staff on design and development standards and best practices.
• Design and implement data security and governance protocols to ensure the accuracy and reliability of data.

Qualifications:

Years of Experience in Related Field: 3+ years of experience as a Data Engineer or a similar role

Education: Bachelor’s degree in Computer Science, Engineering or a related field

Technical/Specialized Knowledge, Skills, and Abilities:

• Technical skills: Expertise in PySpark and data transformation pipelines. Familiarity with AI technologies and cloud platforms (AWS, Azure) is a plus
• Communication: Strong communication skills and a proactive, ownership-driven mindset
• Adaptability: Thrive in a fast-paced, in-office-first startup environment

• Experience with Google Cloud or similar cloud provider 
• Significant experience with open source platforms and technologies.
• Experience with data science and machine learning tools and technologies is a plus.

• A technology-based company with a sense of adventure and a vision for the future. Every door at BlackLine is open. Just bring your brains, your problem-solving skills, and be part of a winning team at the world's most trusted name in Finance Automation!
• A culture that is kind, open, and accepting. It's a place where people can embrace what makes them unique, and the mix of cultural backgrounds and varying interests cultivates diverse thought and perspectives.
• A culture where BlackLiner's continued growth and learning is empowered. BlackLine offers a wide variety of professional development seminars and inclusive affinity groups to celebrate and support our diversity.

BlackLine is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, race, ethnicity, age, religious creed, national origin, physical or mental disability, ancestry, color, marital status, sexual orientation, military or veteran status, status as a victim of domestic violence, sexual assault or stalking, medical condition, genetic information, or any other protected class or category recognized by applicable equal employment opportunity or other similar laws

BlackLine recognizes that the ways we work and the workplace itself has shifted. We innovate in a workplace that optimizes a combination of virtual and in-person interactions to maximize collaboration and nurture our culture. Candidates who live within a reasonable commute to one of our offices will work in the office at least 3 days a week.