Data Engineering Lead for Edge Computing Infrastructure
2 days ago
Armada Systems is an innovative edge computing startup that bridges the digital divide with advanced technology infrastructure.
About the OpportunityWe are seeking a highly motivated Data Engineering Lead to join our Data Platform team and help shape the future of data ingestion, processing, and analysis for our Edge Computing AI Platform.
Job Responsibilities- Design and implement new tools and services that support other teams' data workflows, ingestion, processing, and distribution.
- Collaborate with a diverse group of people to design, discuss, propose, and implement existing data tooling and services.
- Execute on big opportunities and contribute to building a company culture rising to the top of the AI and Edge Computing industry.
- 6+ years of experience in software development.
- Experience with data modeling, ETL/ELT processes, streaming data pipelines.
- Familiarity with data warehousing technologies like Databricks/Snowflake/BigQuery/Redshift and data processing platforms like Spark; working with data warehousing file formats like Avro and Parquet.
- Strong understanding of Storage (Object Stores, Data Virtualization) and Compute (Spark on K8S, Databricks, AWS EMR and the like) architectures used by data stack solutions and platforms.
- Experience with scheduler tooling like Airflow.
- Experience with version control systems like Git and working using a standardized git flow.
- Strong analytical and problem-solving skills, with the ability to work independently and collaboratively in a team environment.
- Professional experience developing data-heavy platforms and/or APIs.
- A strong understanding of distributed systems and how architectural decisions affect performance and maintainability.
- Bachelor's degree in computer science, Electrical Engineering, or related field.
- Experience analyzing ML algorithms that could be used to solve a given problem and ranking them by their success probability.
- Proficiency with a deep learning framework such as TensorFlow or Keras.
- Understanding of MLOps practices and practical experience with platforms like Kubeflow / Sagemaker.
We offer a competitive salary range of $180,000 - $220,000 per year, depending on experience. Additionally, we provide comprehensive benefits, including health insurance, retirement plan, and paid time off.
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