Job Title: Data Engineer

Location: Philadelphia PA

Duration: Long term

Must: Certified Data Modeler

Job Description for Senior Data Engineer roll:

In this role, you will work directly with our Data, Engineering, Operations, Data Science, Go-to-Market, and Finance teams to support the organization's data processing and analytics needs. You will serve as the internal expert on all things data engineering, empowering your peers with your expertise to collectively build a world-class data culture. This is a unique opportunity to directly influence not only our data systems, but also our drones and global operations. The ideal candidate will help us design systems that support the company’s needs today and many years into the future.

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 10+ 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

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Data Engineer