We are looking for a savvy Senior Data Engineer to join our growing team of platform experts. 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.
This is the role for you if you are an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The goal is to support our software developers, database architects, data analysts, and data scientists on data initiatives to ensure optimal data delivery architecture is consistent throughout ongoing projects.
You are self-directed and comfortable supporting the needs of multiple teams, systems, and products. You are excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives. You are a team player who lifts the entire team through collaboration, mentoring, and sharing your experience.
Let’s Talk About Responsibilities
- 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 Python and AWS ‘big data’ technologies like Glue, Lambda, EMR etc.
- 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 AWS regions.
- Work on 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.
Let’s Talk About Qualifications And Experience
- At least 4+ years of total experience and 2+ years of experience in a full-cycle Data Engineer role, who has attained a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field or equivalent working experience
- Excellent Python coding knowledge. Must have previous experience creating/running Python or Pyspark jobs working within AWS Glue
- Experience building and working with AWS Data Lakes
- Experience working on AWS Data Pipeline and CI/CD processes
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with stream-processing systems: Kinesis, Spark-Streaming, etc
- Familiarity with a variety of datasets, structured, semi-structured and unstructured etc.
- Experience building and optimizing ‘big data’ data pipelines, architecture, and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions identify opportunities for improvement.
Joining us is more than saying “yes” to making the world a healthier place. It’s discovering a career that’s challenging, supportive and inspiring. Where a culture driven by excellence helps you not only meet your goals, but also create new ones. We focus on creating a diverse and inclusive culture, encouraging individual expression in the workplace and thrive on the innovative ideas this generates. If this sounds like the workplace for you, apply now!