Staff Engineer - Data Engineering
Early Warning Services11 days ago
San Francisco, CA, USA or Scottsdale, AZ, USAStaff+
Base Salary
$124k - $223k/yr
Responsibilities
- Build data strategy for broad or complex requirements and solve large open-ended problems.
- Lead data and technical architecture, design, prototyping, implementation, planning, and production delivery.
- Develop data warehouses, big-data platforms, real-time and batch processing systems, and scalable distributed solutions.
- Implement and operationalize AI/ML models, including feature engineering, data pipelines, model monitoring, and model lifecycle activities.
- Own features and systems over the long term, improve surrounding systems, and help resolve production issues.
- Develop tests for application quality, performance, and scalability.
- Guide functional teams, represent engineering in cross-functional sessions, and influence technical decisions.
- Improve engineering and data standards, tooling, and processes while supporting risk management and data confidentiality.
Requirements
- Bachelor’s degree in computer science or a related technical field, or equivalent experience typically obtained through the stated education and experience combination.
- Eight or more years of relevant experience.
- Seven or more years developing complex data platforms, distributed systems, SaaS, cloud solutions, or microservices.
- Six or more years developing data warehouses, big-data platforms, structured and unstructured data systems, real-time and batch processing, or data standards.
- Four or more years developing business intelligence solutions.
- Two or more years developing or operationalizing AI/ML models and model lifecycle activities.
- Experience delivering business-critical systems, designing scalable systems, and working collaboratively across teams.
- Experience implementing data warehouses with star or snowflake schemas, SQL Server or equivalent, HDFS, Elasticsearch, ETL processes, and reusable frameworks.
- Experience with Python, Spark, PySpark, R, DataRobot, event-driven architecture, and messaging frameworks such as Pub/Sub, Kafka, or RabbitMQ.
- Working experience with Google Cloud Platform, AWS, or Azure and knowledge of software development lifecycle and DevOps practices.
- Preferred qualifications include an MS or PhD, TensorFlow, SageMaker, scikit-learn, PyCharm, Cloudera, S3, Oracle, Aerospike, Scality S3, AppDynamics, Kubernetes, Databricks, Snowflake, HBase, Hive, Solr, and Scala.
- FinTech experience and knowledge of ACH/EFT and real-time payment networks such as RTP and FedNow are preferred.
- Successful candidates must complete a background and drug screen and meet the stated physical and communication requirements.
Benefits
- Hybrid work model for positions in Scottsdale, San Francisco, Chicago, or New York.
- Base pay is listed by location, with eligibility for a discretionary incentive plan and benefits.
- Medical, dental, and vision coverage, plus HSA and FSA options.
- 401(k) retirement plan with a 100% company Safe Harbor Match on the first 6% deferral immediately upon eligibility.
- Flexible time off for exempt employees or generous PTO for non-exempt employees, plus 11 paid company holidays and a paid volunteer day.
- 12 weeks of paid parental leave and Maven Family Planning support.
- Normal office environment with primarily sedentary work and occasional physical activities as described in the posting.
Tech Stack
Apache HBaseApache HiveApache KafkaApache SparkAWSAzureDatabricksElasticsearchGoogle Cloud PlatformKubernetesMicrosoft SQL ServerPythonRRabbitMQScalascikit-learnSnowflakeTensorFlow
Categories
Data EngineeringML Engineering