Staff Data Engineer

Key Responsibilities:

• Help build, maintain, and scale our data pipelines that bring together data from various internal and external systems into our data warehouse.
• Partner with internal stakeholders to understand analysis needs and consumption patterns.
• Partner with upstream engineering teams to enhance data logging patterns and best practices.
• Participate in architectural decisions and help us plan for the company’s data needs as we scale.
• Adopt and evangelize data engineering best practices for data processing, modeling, and lake/warehouse development.
• Advise engineers and other cross-functional partners on how to most efficiently use our data tools.

Key Qualifications:

• Have 7+ years experience building large scale data platforms
• Experience in Data Engineering, and/or Analytics Engineering, building scalable data warehouses
• Proficient with Dimensional Modeling (Star Schema, Kimball, Inmon) and Data architecture concepts, able to coach and influence others to up-level the craft of Data Engineering
• Fantastic collaboration and communication skills, demonstrated by successful large-scale projects spanning multiple teams
• Advanced SQL skills (ease with window functions, defining UDFs)
• Experienced with Python, Spark for building and maintaining data pipelines & ETL/ELT processes
• Experienced working with dbt and Snowflake, BigQuery, Redshift or other data warehouses
• Experience implementing real-time and batch data pipelines with tight SLOs and complex transformation requirements
• Develop data models, schemas and standards for event dataOptimize data storage and access patterns for fast querying
• Improve data reliability, discoverability and observability
• Familiarity to Data Engineering tooling: ingesting, testing transformations, lineage, orchestration, publishing data, metric layers
• Familiarity with storage layers like Hudi, Delta Lake and Iceberg
• Aptitude for product analysis, dashboarding, and reporting
• Familiarity with infrastructure tooling such as Terraform/Pulumi and worked with Kubernetes
• Proficiency with AWS cloud

Nice To Haves:

• Experience building streaming applications or pipelines using async messaging services or distributed streaming platforms like Apache Kafka
• Knowledge of Airflow or some other orchestration tool
• Experience with Spark or PySparkHave hands-on experience with event-driven architecture and streaming data processing frameworks like Kafka, Spark, Flink
• Experiences with time-series databases like Clickhouse, InfluxDB

What We Offer:

• Competitive salary and stock option incentive program
• Company contribution towards comprehensive benefit packages
• Flexible work arrangements
• Company sponsored team-lunches and company retreats
• International organization that enables you to work across boundaries, travel to different locations and enjoy the dynamics of a rapidly growing startup
• The opportunity to work with a talented and supportive team
• A diverse and inclusive team