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.
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:
Your day to day focus will be dynamic and ever-changing, but you and your team will be driving the business forward by:
- 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 & Experience:
You will have 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.
Your strongest experience will be using the following software/tools:
- 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
You will also be strong in:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with data pipeline and workflow management tools: Luigi, Airflow, AWS Step etc.
- Experience with AWS cloud services: EMR, RDS, Redshift
- 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.
- Strong analytic skills related to working with unstructured datasets.
- 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.
- 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.
Let’s talk about what you can expect:
- A supportive environment that focuses on people development and best practices
- Opportunity to design, influence and be innovative
- Work with global teams and share new ideas
- Be supported both inside and outside of the work environment
- The opportunity to build something meaningful and see a direct positive impact on people’s lives