Description
We are looking for a savvy Data Engineer to join our growing team that supports a data-heavy application.
The hire will be responsible for solutioning and productionizing data storage and retrieval problems to support better performance and scalability.
They will be responsible for expanding and optimizing our data and data pipeline architecture, as well as establishing data flow into downstream systems.
The Data Engineer will support our software developers, business analysts and data scientists on initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
Qualifications:
- 11-13 years of experience in a Data Engineer role
- College degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
- Experience with:
- Big data technologies: DataBricks and/or Snowflake
- Relational SQL and NoSQL databases
- AWS cloud services: EC2, Glue Jobs, RDS, Lambda, EKS
- Stream-processing systems
- Object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- GenAI tools such as Cursor and Copilot
- 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
- Expertise with Performance tuning and query optimization
- 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
- 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
Responsibilities for Data Engineer:
- Create and maintain and continuously improve optimal data pipeline architecture
- Solution performance and scalable data storage and retrieval methods for large datasets for heavy data reliant applications
- Gain knowledge about large, complex data sets that meet functional / non-functional business requirements
- Help the application team with performance tuning of queries and help establish best practices
- 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 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 Product, Business Analysts, Data science 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
- Be attentive to alerts or issues related to the database and take actions to resolve anomalies