Data Engineer

• Pipeline Development: Create and maintain optimal data pipeline architecture by designing, constructing, installing, and maintaining batch and real-time processing systems.
• Data Transformation: Assemble large, complex data sets that meet functional / non-functional business requirements (ETL/ELT).
• Infrastructure Optimization: Identify, design, and implement internal process improvements, including automating manual processes and optimizing data delivery.
• Data Quality: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS/Azure 'big data' technologies.
• Collaboration: Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.

We are seeking a detail-oriented and driven Junior Data Engineer to join our growing data platform team in Phoenix. In this role, you 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. You will support our software developers, database architects, and data analysts on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects., * Experience: 3+ years of experience in a Data Engineering role.

• SQL Mastery: Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL), as well as working familiarity with a variety of databases.
• Programming: Experience performing root cause analysis on internal and external data and processes to answer specific business questions (Python, Scala, or Java).
• Big Data Tools: Experience with big data tools like Hadoop, Spark, or Kafka.
• Cloud Services: Working knowledge of cloud-based data solutions (e.g., AWS Redshift/Glue, Azure Data Factory, or Google BigQuery).
• Data Modeling: Experience with data modeling, data warehousing, and building pipeline monitoring tools., * Bachelor's degree in Computer Science or another quantitative field.
• Experience with workflow management tools like Airflow or Azkaban.
• Familiarity with Stream Processing tools like Spark Streaming or Flink.
• Knowledge of Agile methodologies and CI/CD pipelines.