The Data Engineer will analyze data quality, design prediction algorithms, collaborate with the engineering team, and generate business insights.
This is an exciting position to work on a very talented team of engineers. The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex datasets to ask the right questions and find the right answers. Additionally you enjoy putting the results of your work into meaningful reports that are then presented to the team.
Responsibilities
- Analyze raw data: assessing quality, cleansing, structuring for downstream processing
- Design accurate and scalable prediction algorithms
- Collaborate with engineering team to bring analytical prototypes to production
- Generate actionable insights for business improvements
Qualifications
- Bachelor's degree or equivalent experience in quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
- At least 5 years' of experience in quantitative analytics or data modeling
- Fluency in a programming language (Python and SQL)
- Familiarity with Big Data frameworks and visualization tools such as (Cassandra, Hadoop, Spark, Tableau)
AutoRoboto San Francisco, California, USA Office
San Francisco, California, United States, 94112
Similar Jobs
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead design and implementation of data architecture, ETL/ELT pipelines, data models, warehouses and lakes. Ensure data governance, security, cloud deployments, performance and cost optimization. Coach and manage team members, partner with stakeholders, and drive data-driven solutions for clients.
Top Skills:
Amazon DynamodbAmazon RdsAmazon S3AWSAws CloudformationAws GlueAws LambdaAzureAzure Cosmos DbAzure Data FactoryAzure Data Lake StorageAzure FunctionsAzure Resource ManagerAzure Sql DatabaseDatabricksDevops (Aws/Azure/Gcp)GCPGoogle Cloud FunctionsGoogle Cloud StorageGoogle DataflowGoogle DataprocHadoopIamJavaKafkaPythonScalaSnowflakeSparkSQLTerraform
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead design and implementation of enterprise data architecture and cloud-based data solutions. Manage large data engineering projects, develop data models and pipelines, ensure governance and security compliance, advise clients strategically, and build high-performing inclusive teams.
Top Skills:
AWSAzureDatabricksGCPSnowflake
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Design and implement data architecture and scalable ETL/ELT pipelines on cloud platforms (AWS/Azure/GCP). Analyze complex problems, mentor junior staff, ensure data governance/security compliance, liaise with stakeholders, and deliver high-quality client solutions while developing technical and client-facing skills.
Top Skills:
AWSAws GlueAws LambdaAzureAzure Data FactoryAzure FunctionsDatabricksDataflowEtl/EltGCPGcp DataprocGcp FunctionsScalable Cloud StorageSnowflake
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
