Staff Data Engineer
Posted on 3/22/2024

201-500 employees

Research-based artificial intelligence software provider
Company Overview
ASAPP exists to elevate human performance with AI Native® technology. They focus on addressing complex problems in environments with huge systemic inefficiencies and lots of data where real solutions create significant economic impact.
Robotics & Automation
AI & Machine Learning

Company Stage

Series C

Total Funding





New York, New York

Growth & Insights

6 month growth


1 year growth


2 year growth

New York, NY, USA
Experience Level
Desired Skills
Microsoft Azure
Apache Flink
Apache Spark
Apache Kafka
Data Analysis
Google Cloud Platform
Data Engineering
Data Management
Data & Analytics
  • 7+ years industry experience with clear examples of strategic technical problem solving and implementation
  • Expertise in at least one flavor of SQL. (We use Amazon Redshift, MySQL, Athena and Snowflake)
  • Strong experience with data warehousing (e.g. Snowflake (preferred), Redshift, BigQuery, or similar)
  • Experience with dimensional data modeling and schema design
  • Experience using developer-oriented data pipeline and workflow orchestration (e.g. Airflow (preferred), dbt, dagster or similar)
  • Experience with cloud computing services (AWS (preferred), GCP, Azure or similar)
  • Proficiency in a high-level programming language, especially in terms of reading and comprehending other developers’ code and intentions. (We use Python, Scala, and Go)
  • Deep technical knowledge of data exchange and serialization formats such as Protobuf, YAML, JSON, and XML
  • Familiarity with BI & Analytics tools (e.g. Looker, Tableau, Sisense, Sigma computing or similar)
  • Familiarity with streaming data technologies for low-latency data processing (e.g. Apache Spark/Flink, Apache Kafka, Snowpipe or similar)
  • Familiarity with Terraform, Kubernetes and Docker
  • Understanding of modern data storage formats and tools (e.g. parquet, Avro, Delta Lake)
  • Knowledge of modern data design and storage patterns (e.g. incremental updates, partitioning and segmentation, rebuilds and backfills)
  • Experience working at a startup preferred
  • Excellent communication skills - (Slack/Email/Documents)
  • Experienced with end user management & communication (cross team as well as external)
  • Must thrive in a fast paced environment and be able to work independently with urgency
  • Can work effectively remotely (able to be proactive about managing blockers, proactive on reaching out and asking questions, and participating in team activities)
  • Experienced in writing technical data design docs (pipeline design, dataflow, schema design)
  • Can scope and breakdown projects, communicate and collaborate progress and blockers effectively with your manager, team, and stakeholders
  • Good at task management & capacity tracking (JIRA (preferred))
  • Lead the batch analytics team by providing the groundwork to modernize our data analytics architecture
  • Design and maintain our data warehouse to facilitate analysis across hundreds of systems events
  • Rethink and influence strategy and roadmap for building efficient data solutions and scalable data warehouses
  • Review code for style and correctness across the entire team
  • Write production-grade Redshift, Athena, Snowflake & Spark SQL queries
  • Manage and maintain Airflow ETL jobs
  • Test query logic against sample scenarios
  • Work across teams to gather requirements and understand reporting needs
  • Investigate metric discrepancies and data anomalies
  • Debug and optimize queries for other business units
  • Review schema changes across various engineering teams
  • Maintain high-quality documentation for our metrics and data feeds
  • Work with stakeholders in Data Infrastructure, Engineering, Product and Customer Strategy to assist with data-related technical issues and build scalable cross platform reporting framework
  • Participate in, and co-manage our on-call rotation to keep production pipelines up and running