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Data Developer

San Francisco

SpringCube

Full-time - Senior Engineer

Social Media & Internet Platforms

Posted 2 weeks ago

$160,000 - $200,000

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Job Description

This job was selected by the SpringCube team to help AI, Data and Cloud Engineers discover relevant San Francisco Bay Area employers. Sign up to view the full employer details and apply directly with the hiring company.

Company Overview
A growing mobile communications company is seeking an experienced Data Developer to help build and maintain scalable data platforms that support business intelligence, data products, and AI/ML initiatives. The organization focuses on improving access to communication services while fostering an engineering environment centered on innovation, collaboration, and data-driven decision-making.

Summary
The Data Developer will own the design, development, and maintenance of data platforms, including data warehouses, pipelines, integrations, and data models. The role works across engineering, infrastructure, and business teams to build reliable data systems and enable faster access to information for insights, analytics, and AI/ML applications.

Responsibilities

  • Own the data warehouse, data pipelines, and integration points connecting various business systems.
  • Design, develop, maintain, and optimize batch and real-time data pipelines.
  • Recommend and implement improvements to existing data platforms and processes.
  • Develop and manage data models that support AI and machine learning products.
  • Collaborate with engineering and infrastructure teams to improve access to data for business insights and decision-making.
  • Communicate data modeling and architecture processes to cross-functional stakeholders.
  • Identify and implement process improvements across the data platform.
  • Leverage AI-powered development tools throughout system design, architecture, implementation, testing, debugging, documentation, and operational analysis.
  • Continuously improve the use of AI tools to increase engineering efficiency, code quality, and technical decision-making.

Qualifications

  • 3–5 years of experience working with data warehouses, data lakes, and ETL architectures.
  • Experience with technologies such as Databricks and Iceberg is preferred.
  • Hands-on experience with cloud data warehouses such as Snowflake.
  • Strong proficiency in Python and SQL.
  • At least 2 years of experience working with Airflow and Spark.
  • Experience developing scalable, real-time data pipelines using Python or Scala, SQL, and distributed processing frameworks such as Spark or Flink.
  • Exposure to AWS platforms and services such as EKS, MSK, and MWAA is preferred.
  • Experience building data features using Snowflake, dbt, and Python to support real-time AI/ML inference.
  • Experience working in fast-growing environments with evolving data requirements.
  • Strong ownership and ability to initiate tasks and drive them through completion.
  • Respectfully candid communication style with the ability to collaborate effectively across teams.
  • Highly organized, dependable, and structured approach to work.

Disclaimer
SpringCube curates tech job listings from various company websites to support tech professionals globally.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
3. To Apply: Click the “Apply” button to be redirected to the hiring company’s application page for this job.
4. No Liability: SpringCube is not liable for inaccuracies.

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