We are seeking a Senior Data Engineer to become a part of our team. This presents an exceptional opportunity to join us during its scaling phase and contribute significantly to our growth and success. As a fast-evolving, product-led startup, we are committed to revolutionizing efficiency, intelligence, collaboration, and safety with our unique speech AI technology. Supported by substantial investments from leading venture capitalists, including New Era Capital Partners and Hamilton Lane, we are strategically positioned to create a profound impact in the industry.
In the role of Senior Data Engineer, you will be crucial in overseeing all aspects of data management, including process establishment, tool selection, and database management, collaborating with teams in Data Science, Backend Development, Project Management, and DevOps. Reporting to the Data Engineering Team Leader, your proactive involvement will be key in advancing our projects, with a primary focus on developing robust, efficient data pipelines utilizing the latest technologies. You will also work in tandem with various teams to elevate awareness, stimulate demand, and encourage the adoption of our solutions.
Working Hybrid- 3 days a week from the office
Responsibilities:
Play a pivotal role in defining our Data Model and building the data pipelines for our Data Lake.
Work in close collaboration with the Data Science team to develop data pipelines for AI model performance monitoring.
Design, automate, and implement complex end-to-end data pipelines using Python, DBT, and Prefect.
Act as the gatekeeper to ensure data quality across all data pipelines.
Take full ownership of projects, from proof of concept to production deployment.
Contribute to a diverse range of projects, focusing on automating data processes with various technologies and tools.
Define access patterns for all data layers, including both operational and analytical layers.
In the role of Senior Data Engineer, you will be crucial in overseeing all aspects of data management, including process establishment, tool selection, and database management, collaborating with teams in Data Science, Backend Development, Project Management, and DevOps. Reporting to the Data Engineering Team Leader, your proactive involvement will be key in advancing our projects, with a primary focus on developing robust, efficient data pipelines utilizing the latest technologies. You will also work in tandem with various teams to elevate awareness, stimulate demand, and encourage the adoption of our solutions.
Working Hybrid- 3 days a week from the office
Responsibilities:
Play a pivotal role in defining our Data Model and building the data pipelines for our Data Lake.
Work in close collaboration with the Data Science team to develop data pipelines for AI model performance monitoring.
Design, automate, and implement complex end-to-end data pipelines using Python, DBT, and Prefect.
Act as the gatekeeper to ensure data quality across all data pipelines.
Take full ownership of projects, from proof of concept to production deployment.
Contribute to a diverse range of projects, focusing on automating data processes with various technologies and tools.
Define access patterns for all data layers, including both operational and analytical layers.
Requirements:
Minimum of 5 years' experience as a Data Engineer.
Proficient in Python and SQL.
Experience with AirFlow/Prefect and Athena for workflow management.
Familiarity with non-relational databases such as Athena, Presto, and DynamoDB.
Skilled in using AWS cloud compute and storage services.
Proficient with Docker and Kubernetes for containerization and orchestration.
Demonstrated experience in data processing and ETL in production settings.
Capable of handling complex data sets effectively.
Knowledge of data visualization and analytics is a plus.
B.Sc degree in Computer Science, Mathematics, Statistics, or Physics – an advantage
Strong team player with excellent collaborative abilities.
Ideal for those who excel in dynamic, fast-paced environments and possess self-direction, creativity, and determination.
Minimum of 5 years' experience as a Data Engineer.
Proficient in Python and SQL.
Experience with AirFlow/Prefect and Athena for workflow management.
Familiarity with non-relational databases such as Athena, Presto, and DynamoDB.
Skilled in using AWS cloud compute and storage services.
Proficient with Docker and Kubernetes for containerization and orchestration.
Demonstrated experience in data processing and ETL in production settings.
Capable of handling complex data sets effectively.
Knowledge of data visualization and analytics is a plus.
B.Sc degree in Computer Science, Mathematics, Statistics, or Physics – an advantage
Strong team player with excellent collaborative abilities.
Ideal for those who excel in dynamic, fast-paced environments and possess self-direction, creativity, and determination.
This position is open to all candidates.