Data Engineering Manager
ASAPP
 Buenos Aires, TX
At ASAPP, our mission is to solve complex and challenging problems by building transformative machine learning-powered products. We leverage artificial intelligence to address significant challenges that share three common characteristics: huge economic scale, systemic inefficiencies, and tremendous amounts of data. Our talented teams that drive our product innovation and development are located in New York City, San Francisco, Mountain View, and Buenos Aires.

We’re looking to hire a Data Engineering Manager with a passion for analytics to create and enhance sophisticated metrics and reporting to help monitor and continuously improve our systems. You’ll also serve to bridge the gap between infrastructure engineering, data science, and business intelligence teams by building analytic data feeds for both our business partners and internal stakeholders, and we’ll lean on you to define event specifications, automate data collection, validation, and usage wherever and whenever possible. You’ll play a key role in influencing the direction of our data analytics platform and play an integral role in making the most out of the massive amounts of events we log and train machine learning models with every day. All of this while you lead the BA Data Engineering team in designing, building, and maintaining our mission-critical core data analytics platform. You will be mentoring, coaching and inspiring software engineers on the team to take on new technical challenges and grow their careers. You will lead the team in looking at problems in new ways and inventing simple solutions to complex problems.

What you'll do

  • You'll be responsible for growing and developing an incredible team of talented and motivated engineers with high expectations around individual ownership and impact
  • You'll foster a healthy and collaborative culture that embodies ASAPP's values
  • You'll ensure your team delivers extraordinary output, and continuously seeks ways to make an outsized impact
  • You'll set direction for the team, anticipate strategic and scaling-related challenges via thoughtful long-term planningImplement, manage, and scale data pipelines for analytics, reporting, and machine learning
  • Collaborate with other engineering teams, product managers, and data analysts to understand needs and deliver deeper insights about existing data
  • Create, optimize, and maintain efficient ETL jobs in Airflow
  • Investigate metric discrepancies and data anomalies

What you'll need

  • 4+ years of management experience with an engineering team
  • 8+ years of development experience
  • Experience and maturity in building distributed, scalable systems
  • Strong experience with either Java, Scala, Go, Python
  • Experience with Analytics, SQL, No-SQL, AWS, GCloud, Spark, Kafka, Airflow
  • Deep technical knowledge of data exchange and serialization formats such as Protobuf, YAML, JSON, and XML
  • Familiarity with workflow management systems such as Apache Airflow or Oozie

What we'd like to see

  • A Bachelor’s Degree in a field of science, technology, engineering, or math or equivalent hands-on experience
  • Previous experience managing the analytical feeds within a data infrastructure, data engineering, data science, or data analyst role
  • Experience with A/B testing, anomaly detection, or time series analysis

Perks

  • Competitive compensation
  • Stock options
  • Free lunch daily
  • OSDE 410 for the family group
  • Fully stocked kitchen
  • Wellness perks
  • Mac equipment
  • 3 weeks vacation
  • Training and development
  • English lessons
ASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at jobs@asapp.com to obtain assistance.