Data Engineer - Zeitworks

Zeitworks Team
Zeitworks is a new start-up sitting at the center of the fastest growing enterprise software segments: RPA, Process Mining, BPM, in a new category we’re calling Intelligent Ops. Looking beyond automation, Zeitworks automatically discovers, monitors and documents all an organization’s business processes, with zero disruption providing real-time business recommendations to business leaders. We have an experienced enterprise leadership team, and the backing of premiere venture capital investors.

We’re looking for an experienced senior data engineer to join our Seattle based engineering team to build a modern analytics stack and scalable, resilient data pipelines. You will have a great opportunity to make an impact at a young and growing company in their delivery of enterprise analytics, data science, and automation functions. If you are familiar with building environments to enable data scientists, enjoy finding creative solutions to data problems, and enthusiastic about learning or improving your skills using best practices in data modeling and ETL/ELT process for delivering multi-dimensional datasets, we have interesting challenges for you. Preference will be given to local candidates.

    • Implement data ingestion routines that deliver raw data in a usable format
    • Help design and implement a modern workflow orchestration platform
    • Automate data processes across multiple internal teams
    • Help with developing, constructing, test, and maintenance of BI&A data architecture
    • Stay up-to-date with advances in data persistence and big data technologies and run pilots to design the data architecture to scale with the increased data sets
    • Partner with data scientists and product management, operations, sales, and engineering to build and verify hypotheses to improve the business performance.
    • Manage weekly business reports via dashboards and paper the analyses of daily, weekly, and monthly reporting of performance via Key Performance Indicators.
    • Provide input and recommendations on technical issues and think through trade-offs and risks and communicate them with team/business stakeholders
    • Work with stakeholders to establish requirements and explain the benefits/risks of proposed approaches
    • Recommend and implement solutions to improve data reliability, efficiency, and quality


    • 3+ years of professional experience
    • BS degree in computer science or quantitative discipline
    • Experience with common and modern data stores (RDBMS, cloud native data lakes and warehousing technologies, NoSQL DBs, etc.)
    • Significant experience with SQL
    • Significant experience building data pipelines with Python
    • Significant experience with ETL processes, patterns and technologies
    • Experience with modern orchestration platforms like Airflow
    • Experience with modern data modeling concepts


    • Experience with IaaS providers (AWS, Azure, GCP)
    • Experience with data science and statistical concepts
    • Experience with container technologies (Docker/Kubernetes)
    • Experience with message broker technologies (e.g. Kafka)
    • Experience with large scale data processing and analytics technologies (e.g. Hadoop, Spark, Flink, etc.)
    • Advanced degree in a quantitative discipline
    • Interest in implementing DataOps concepts
We founded Zeitworks to help people get the most out of their lives. We are a team of data scientists, systems engineers, designers, and business analysts and we are building Zeitworks to help businesses leaders make informed choices about improving their business, empowering their organization and making their people happier by helping them focus on the things that matter the most.

Zeitworks values inclusion and diversity and aspires to be among the tech industry’s most inclusive work environments. We believe diversity at all levels will enable us to best accomplish our mission. We are committed to diversity in our workforce and are a proud equal opportunity employer we do not make hiring or employment decisions on the basis of race, color, religion, creed, gender, national origin, age, sex, gender expression or identity, sexual orientation, or disability status, marital status, or veteran status.