Staff Data Engineer
About The Position
It's fun to work in a company where people truly believe in what they're doing! At BlackLine, we're committed to bringing passion and customer focus to the business of enterprise applications. Since being founded in 2001, BlackLine has become a leading provider of cloud software that automates and controls the entire financial close process. Our vision is to modernize the finance and accounting function to enable greater operational effectiveness and agility, and we are committed to delivering innovative solutions and services to empower accounting and finance leaders around the world to achieve Modern Finance. Being a best-in-class SaaS Company, we understand that bringing in new ideas and innovative technology is mission critical. At BlackLine we are always working with new, cutting edge technology that encourages our teams to learn something new and expand their creativity and technical skillset that will accelerate their careers. Work, Play and Grow at BlackLine!
Requirements
- 3+ years of experience as a Data Engineer or a similar role
- Bachelor’s degree in Computer Science, Engineering or a related field
- Expertise in PySpark and data transformation pipelines.
- Familiarity with AI technologies and cloud platforms (AWS, Azure) is a plus
- Strong communication skills and a proactive, ownership-driven mindset
- Adaptability: Thrive in a fast-paced, in-office-first startup environment
Nice To Haves
- 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.
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.
Benefits
- short-term and long-term incentive programs
- robust offering of benefit and wellness plans
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What This Job Offers
Job Type
Full-time
Career Level
Senior
