Data Engineering Lead for Edge Computing Infrastructure

2 days ago


Thiruvananthapuram, Kerala, India Armada Systems Full time

Armada Systems is an innovative edge computing startup that bridges the digital divide with advanced technology infrastructure.

About the Opportunity

We 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.
Preferred Qualifications
  • 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.
Additional Skills and Experience
  • 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.
Compensation and Benefits

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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