Manager, Data Engineering

Company Description

Hi there! We’re Razorfish. We’ve been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What’s different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.

Job Description

We are looking for a savvy Data Engineer to join our growing team. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or even re-designing client data architecture to support next generation of products and data initiatives.

Responsibilities for Data Engineer

• Create and maintain optimal data pipeline architecture, including table design.
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and (GCP, AWS, Azure, Snowflake)  ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing advanced analytics and data models.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Qualifications

Qualifications for Data Engineer

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 3-5 years of experience in a Data Engineer role, who has attained an undergraduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
  • Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
  • Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
  • Experience with big data tools: Hadoop, Spark, Kafka, etc.
  • Experience with AWS cloud services: EC2, EMR, RDS, Redshift, Athena
  • Experience with GCP cloud services: BigQuery, GCS, Cloud SQL, ML, Pub/Sub, DataProc
  • Experience with Azure cloud services: DataBricks, 
  • Experience with stream-processing systems: Storm, Spark-Streaming, etc.
  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
  • Experience with data architecture creating staging and final table design.
  • Experience creating ERD / Data Dictionary documentation.

Additional Information

The Power of One starts with our people!  To d