As a Senior Data Engineer, you’ll be a part of our growing engineering team and help our core data layer, which includes data services, core application schema(s), data lake, data connectors, and data transformation.
- You’ll have the chance to partner closely with our engineering teams, data analysts, product management, and business operations and be the glue that connects the dots.
- We are looking for an experienced Data professional who is a problem solver, a logical thinker, and passionate about everything relating to data and analytics.
- Create and maintain optimal data pipeline architecture.
- 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, Snowflake, and AWS ‘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.
- Keep our data separated and secure across national boundaries through multiple data centers and Snowflake, AWS regions.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Minimum of 7 years of experience in a Data Engineer role.
- 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.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with object-oriented/object function scripting languages: Python, SQL, Scala, Spark-SQL, etc.Experience with Kafka, Talend, and Stream sets.
Nice to have experience with big data tools:
Hadoop, Spark, etc.Nice to have experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
